This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision Next revision | Previous revision Next revision Both sides next revision | ||
|
teaching:mfe:is [2014/06/03 11:22] svsummer [Master Thesis in Collaboration with DPI 24/7 Media Publishing] |
teaching:mfe:is [2019/06/07 14:56] svsummer [Graph Indexing for Fast Subgraph Isomorphism Testing] |
||
|---|---|---|---|
| Line 1: | Line 1: | ||
| - | ====== MFE 2014-2015 : Web and Information Systems ====== | + | ====== MFE 2019-2020 : Web and Information Systems ====== |
| ===== Introduction ===== | ===== Introduction ===== | ||
| Line 18: | Line 18: | ||
| ===== Master Thesis in Collaboration with Euranova ===== | ===== Master Thesis in Collaboration with Euranova ===== | ||
| - | Our laboratory performs collaborative research with Euranova R&D (http://euranova.eu/). The list of subjects proposed for this year by Euranova can be found | + | Our laboratory performs collaborative research with Euranova R&D (http://euranova.eu/). The list of subjects proposed for this year by Euranova can be found [[https://research.euranova.eu/wp-content/uploads/proposals-thesis-2019.pdf|here]]. |
| - | {{:teaching:mfe:mt2014_euranova.pdf|here}} | + | |
| These subject include topics on distributed graph processing, processing big data using Map/Reduce, cloud computing, and social networks. | These subject include topics on distributed graph processing, processing big data using Map/Reduce, cloud computing, and social networks. | ||
| Line 25: | Line 25: | ||
| * Contact : [[ezimanyi@ulb.ac.be|Esteban Zimanyi]] | * Contact : [[ezimanyi@ulb.ac.be|Esteban Zimanyi]] | ||
| - | ===== Master Thesis in Collaboration with DPI 24/7 Media Publishing ===== | ||
| - | The goal of the thesis is to set up a Saas / Paas solution for the deployement of the dpi 24/7 media publishing distribution in a Heroku-like style. | ||
| - | During this master thesis you will not only realize a theoretical and technological analysis of the problem of such a deployment but also implement a concrete solution for the dpi 24/7 distribution. | ||
| - | From a technical point of view you will : | + | ===== Multi-query Optimization in Spark ===== |
| - | * Develop a service using Docker and Dokku for the on-demand deployment of instances of the DPI 24/7 distribution (full stack architecture) | + | |
| - | * Realize performance tests of the developed service | + | |
| - | * Study the different options of the Paas mode (full stack or elastic deployment) | + | |
| - | Second, you will analyze the different existing solutions for the orchestration of an elastic virtualization architecture. | + | Distributed computing platforms such as Hadoop and Spark focus on addressing the following challenges in large systems: (1) latency, (2) scalability, and (3) fault tolerance. Dedicating computing resources for each application executed by Spark can lead to a waste of resources. Unified distributed file systems such as Alluxio has provided a platform for computing results among simultaneously running applications. However, it is up to the developers to decide on what to share. |
| - | Technology used by the DPI 24/7 distribution : Linux, Varnish, NginX, Php-fpm, Mysql (in background Tomcat, SOLR). | + | The objective of this master thesis is to optimize various applications running on a Spark platform, optimize their execution plans by autonomously finding sharing opportunities, namely finding the RDDs that can be shared among these applications, and computing these shared plans once instead of multiple times for each query. |
| - | Virtualization technology : Container virtualization and deployment with Dokku | + | **Deliverables** of the master thesis project |
| + | * An overview of the Apache Spark architecture. | ||
| + | * Develop a performance model for queries executed by Spark. | ||
| + | * An implementation that optimizes queries executed by Spark and identify sharing opportunities. | ||
| + | * An experimental validation of the developed system. | ||
| - | Interested? DIP 27/7 Contact [[ddu@audaxis.com|Dimitri Dujardin]]. Academic Supervisor [[svsummer@ulb.ac.be|Stijn Vansummeren]] | + | **Interested?** Contact : [[svsummer@ulb.ac.be|Stijn Vansummeren]] |
| - | ===== Automatic detection of name variations ===== | + | **Status**: available |
| - | Toon Calders (WIT) | + | |
| - | For this project a large data collection consisting of historical birth, death, and marriage certificates of the province of North-Brabant in the Netherlands is available. This collection contains certificates for about 3 million people, from 1580 until 1955. This collection of paper documents has been indexed by volunteers. For many of the certificates (unfortunately the index is not complete yet), the names of the people involved in it, and their role have been recorded in a database. Consider for instance the following example of an index entry for a death certificate: | + | ===== Graph Indexing for Fast Subgraph Isomorphism Testing ===== |
| - | ^ Death certificate ^^ | + | There is an increasing amount of scientific data, mostly from the bio-medical sciences, that can be represented as collections of graphs (chemical molecules, gene interaction networks, ...). A crucial operation when searching in this data is that of subgraph isomorphism testing: given a pattern P that one is interested in (also a graph) in and a collection D of graphs (e.g., chemical molecules), find all graphs in G that have P as a subgraph. Unfortunately, the subgraph isomorphism problem is computationally intractable. In ongoing research, to enable tractable processing of this problem, we aim to reduce the number of candidate graphs in D to which a subgraph isomorphism test needs to be executed. Specifically, we index the graphs in the collection D by means of decomposing them into graphs for which subgraph isomorphism *is* tractable. An associated algorithm that filters graphs that certainly cannot match P can then formulated based on ideas from information retrieval. |
| - | |Deceased |Johanna Louise Fredrika Frans | | + | |
| - | |Relation of the deceased |Gerard Cornelius Reincke de Sitter | | + | |
| - | |Father of the deceased |Carl Ludwig Frans | | + | |
| - | |Mother of the deceased |Alida Philippina Zehender | | + | |
| - | |Type of deed |death certificate | | + | |
| - | |Number of deed |5 | | + | |
| - | |Place |Beers | | + | |
| - | |Date of decease |26-02-1825 | | + | |
| - | |Period |1825 | | + | |
| - | |Contains |Overlijdensregister 1825 | | + | |
| - | |Number of inventory |50 | | + | |
| - | |Record number |456 | | + | |
| - | There are, however, several problems with the data recorded by the volunteers: | + | In this master thesis project, the student will emperically validate on real-world datasets the extent to which graphs can be decomposed into graphs for which subgraph isomorphism is tractable, and run experiments to validate the effectiveness of the proposed method in terms of filtering power. |
| - | - Volunteers made mistakes when recording the names | + | |
| - | - Natural name variations occur; for instance, during the Napoleonic era, Willem preferred to be called Guillaume. After the French left the Netherlands, Willem became Willem again. Other, less spectacular variations: Fredrika versus Frederika. | + | |
| - | - Another source of variation is the granularity at which locations are reported. Sometimes locations have been reported at suburb or even neighborhood level, whereas in other records only the city is reported. | + | |
| - | - Also the original data contained errors. For instance, the order of names may have been swapped. | + | |
| - | The goal of this graduation project is to automatically detect name variations for location and person names, using statistical and data mining methods. Because of the large size of the database it is very likely that most name variations occur frequently. In a pilot study, it was shown that name variations could be detected by finding pairs of full names sharing most surnames, but not all. The differences often were name variations. Your task will be to extend this approach to also include locations, and exploit additional background knowledge such as: for most birth certificates there is a matching death certificate, no one has more than one birth and death certificate, etc. | + | **Interested?** Contact : [[stijn.vansummeren@ulb.ac.be|Stijn Vansummeren]] |
| - | This project has a large research component, so your creative input will be required as well. For this project it is absolutely not necessary to speak or understand Dutch. | + | |
| - | Interested? Contact [[toon.calders@ulb.ac.be|Toon Calders]] | + | **Status**: taken |
| - | ===== Analyzing state-of-the-art technology for handwritten text recognition in a practical case study ===== | ||
| - | Toon Calders (WIT) and Olivier Debeir (LISA) | ||
| - | The goal of this project is to study the applicability of current state-of-the-art text recognition tools in the following practical application. Consider the following two exemplary documents: | + | =====Extending SPARQL for Spatio-temporal Data Support===== |
| - | [[https://dl.dropbox.com/u/5119252/MFE/069-50-3165-1813-00009.jpg]] \\ | + | [[http://www.w3.org/TR/rdf-sparql-query/|SPARQL]] is the W3C standard language to query RDF data over the semantic web. Although syntactically similar to SQL, SPARQL is based on graph matching. In addition, SPARQL is aimed, basically, to query alphanumerical data. |
| - | [[https://dl.dropbox.com/u/5119252/MFE/069-50-3165-1815-00003.jpg]] | + | Therefore, a proposal to extend SPARQL to support spatial data, called [[http://www.opengeospatial.org/projects/groups/geosparqlswg/|GeoSPARQL]], has been presented to the Open Geospatial Consortium. |
| + | |||
| + | In this thesis we propose to (1) perform an analysis of the current proposal for GeoSPARQL; (2) a study of current implementations of SPARQL that support spatial data; (3) implement simple extensions for SPARQL to support spatial data, and use these language in real-world use cases. | ||
| + | |||
| - | These two documents are scans of birth certificates (actually both are 2 birth certificates) from the Dutch city Grave. We have a huge collection of such paper documents; about 3 million, of which several tens of thousands have been scanned. Furthermore, we have an index on these documents, created by volunteers. This index contains, for the birth certificate, the name of the child, the name of the father and mother, and the witnesses. As you can see in the documents, however, much more information is available. Your task is to answer the following question: is it realistic, given the current state-of-the-art to do automatic recognition of hand-written texts such as these certificates? Most of the documents are very structured, with limited number of possible values (age of a person, profession), and there is a huge amount of training data; the names of all people have been indexed, usually the handwriting is consistent throughout a whole book with certificates. This graduation project includes a thorough literature study and experimentation with (original combinations of) state-of-the-art image recognition techniques adapted to our specific case. The project will be carried out in collaboration with the research labs WIT and LISA. | + | * Contact: [[ezimanyi@ulb.ac.be|Esteban Zimányi]] |
| - | Interested? Contact [[toon.calders@ulb.ac.be|Toon Calders]] | ||
| - | ===== Process Mining on Company Data for Detecting Security Breaches ===== | + | ====== MFE 2019-2020 : Spatiotemporal Databases ====== |
| - | Toon Calders (WIT) | + | Moving object databases (MOD) are database systems that can store and manage moving object data. A moving object is a value that changes over time. It can be spatial (e.g., a car driving on the road network), or non-spatial (e.g., the temperature in Brussels). Using a variety of sensors, the changing values of moving objects can be recorded in digital formats. A MOD, then, helps storing and querying such data. A couple of prototypes have also been proposed, some of which are still active in terms of new releases. Yet, a mainstream system is by far still missing. Existing prototypes are merely research. By mainstream we mean that the development builds on widely accepted tools, that are actively being maintained and developed. A mainstream system would exploit the functionality of these tools, and would maximize the reuse of their ecosystems. As a result, it becomes more closer to end users, and easily adopted in the industry. |
| - | According to a recent report of Price Waterhouse Cooper, the most common source of security incidents are current employees, followed at a distance by former employees and only after that truly external threats such as hactivists. [http://www.pwc.com/gx/en/consulting-services/information-security-survey/giss.jhtml?region=&industry=] This observation leads to the conclusion that in an intelligent security event management system, should also concentrate on internal threats to security. | + | In our group, we are building MobilityDB, a mainstream MOD. It builds on PostGIS, which is a spatial database extension of PostgreSQL. MobilityDB extends the type system of PostgreSQL and PostGIS with ADTs for representing moving object data. It defines, for instance, the tfloat for representing a time dependant float, and the tgeompoint for representing a time dependant geometry point. MobilityDB types are well integrated into the platform, to achieve maximal reusability, hence a mainstream development. For instance, the tfloat builds on the PostgreSQL double precision type, and the tgeompoint build on the PostGIS geometry(point) type. Similarly MobilityDB builds on existing operations, indexing, and optimization framework. |
| - | The goal of the thesis is to analyze the possibility of using process mining to help in the detection of silent attacks. We will concentrate on company-specific data. From this data typical behavior will be detected and modeled as a process or workflow. We consider three aspects of a workflow: the actor(s), the resources, and the activities. By modeling the normal behavior in the system we are able to detect deviating cases. Based on historical data, the goal is to build models of typical behavior, including the use of resources such as patient records. Such a system would be able to detect for instance if a certain patient record is consulted much more often than usual, or by more people, or outside of the normal workflow (e.g., only reading information, but not writing). Such a pattern could indicate unjustified access to for instance the patient record of a famous patient. | + | |
| - | For modeling the workflows, we propose the use of process mining (Van der Aalst, 2011). Process mining is a state-of-the-art technology concerned with the automatic extraction of process models from event logs. Consider, e.g., a hospital registering all activities that are carried out for the treatment of patients, ranging from the admission, various measurements being taken from the patient, medicine administered, surgical procedures, to the resignation of the patient. Process mining could be used to extrapolate from these examples, a common model of how the hospital deals with a patient. There are several applications of process mining; first it can be used to improve the processes by standardizing them; many companies and organizations may only have informal procedures. By process mining the process logs are used to extract a general model of the actual business processes. Such a model can guide the automation process. | + | |
| - | In this thesis the goal is to analyze how process mining could be used for anomaly detection; how can the discovered models be used to detect abnormal behavior in a company network? Much like in credit card fraud detection, the approach is to first model normal behavior, in this case using process mining, in order to detect diverging behavior that could indicate security breaches in the network. | + | |
| - | Van der Aalst, W. M. (2011). Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer. | + | This is all made accessible via the SQL query interface. Currently MobilityDB is quite rich in terms of types and functions. It can answer sophisticated queries in SQL. The first beta version has been released as open source April 2019 (https://github.com/ULB-CoDE-WIT/MobilityDB). |
| + | The following thesis ideas contribute to different parts of MobilityDB. They all constitute innovative development, mixing both research and development. They hence will help developing the student skills in: | ||
| + | * Understanding the theory and the implementation of moving object databases. | ||
| + | * Understanding the architecture of extensible databases, in this case PostgreSQL. | ||
| + | * Writing open source software. | ||
| - | Interested? Contact [[toon.calders@ulb.ac.be|Toon Calders]] | ||
| - | ===== Mining patterns for compression ===== | + | =====JDBC driver for Trajectories===== |
| - | Toon Calders (WIT) | + | An important, and still missing, piece of MobilityDB is Java JDBC driver, that will allow Java programs to establish connections with MobilityDB, and store and retrieve data. This thesis is about developing such a driver. As all other components of PostgreSQL, its JDBC driver is also extensible. This documentation gives a good explanation of the driver and the way it can be extended: |
| + | https://jdbc.postgresql.org/documentation/head/index.html | ||
| + | It is also helpful to look at the driver extension for PostGIS: | ||
| + | https://github.com/postgis/postgis-java | ||
| - | Data mining is the research discipline that studies the extraction of information from large amounts of data. One of the typical data mining tasks is pattern mining where we try to find regularities that occur frequently in a dataset. The prototypical example is that of a supermarket storing for every customer visiting the supermarket, the transaction; that is, the set of items that were bought by that customer. The frequent itemset mining problem now is to detect which combinations of products were more often sold together than a given threshold. One of the major problems of pattern mining algorithms, however, is the enormous amount of redundant patterns they generate; for instance, very popular items, such as toilet paper, tend to appear in many frequent combinations purely due to chance. In order to deal with this problem, techniques based upon compression and minimum description length were proposed to reduce the number of patterns. The rationale behind the minimal description length principle is that a set of patterns that describes well what is happening in the dataset should allow for a good compression. For a collection of patterns, the quality is measured as the description length of the patterns plus the size of the data compressed with these patterns. For instance, if the pattern {bread, milk, butter} has a high frequency, we could opt to replace every occurrence of this pattern by a special code, effectively reducing the encoding length of the data. Surprisingly, however, the MDL principle was until now only used to rule out redundant patterns, and it has not been researched yet how well the discovered patterns actually do compress the data as compared to compression algorithms such as Lempel–Ziv–Welch. | + | As MobilityDB build on top of PostGIS, the Java driver will need to do the same, and build on top of the PostGIS driver. Mainly the driver will need to provide Java classes to represent all the types of MobilityDB, and access the basic properties. |
| - | Hence, in this highly research oriented graduation project, two research questions are central: (1) How good do non-redundant pattern sets based on MDL allow compressing data, and (2) Can we extract useful patterns from existing compression algorithms? | + | |
| - | Interested? Contact [[toon.calders@ulb.ac.be|Toon Calders]] | + | **Interested?** |
| + | * Contact : [[ezimanyi@ulb.ac.be|Esteban Zimanyi]] | ||
| - | ===== Pattern Mining for Object Tracking ===== | + | **Status**: available |
| - | Toon Calders (WIT) | + | |
| - | Pattern mining techniques are more and more often used in computer vision | + | =====Mobility data exchange standards===== |
| - | to obtain features that are more discriminative than those extracted | + | Data exchange standards allow different software systems to integrate together. Such standards are essential in the domain of mobility. Consider for example the case of public transportation. Different vehicles (tram, metro, bus) come from different vendors, and are hence equipped with different location tracking sensors. The tracking software behind these vehicle use different data formats. These software systems need to push real time information to different apps. To support the passengers, for example, there must be a mobile or a Web app to check the vehicle schedules and to calculate routes. This information shall also be open to other transport service providers and to routing apps. This is how google maps, for instance, is able to provide end to end route plans that span different means of transport. |
| - | using computer vision algorithms. This is true for example in content-based | + | |
| - | images/videos retrieval, indexing, classification, tracking, etc. However, the main | + | |
| - | drawback of using traditional pattern mining techniques is their inefficiency when | + | |
| - | dealing with huge set of data (for example provided by Google image or Youtube | + | |
| - | for videos) or when trying to tackle real-time analysis problems. The data mining | + | |
| - | community has been working on the “Big Data” problem for many years coming | + | |
| - | up with promising solutions such as stream mining. The aim of this project | + | |
| - | is to explore the possibility of using pattern mining in data streams for the (real-time) analysis of videos and, in particular, for object tracking. | + | |
| - | For more extensive information regarding the context and problem setting, see the following paper: | + | The goal of this thesis is to survey the available mobility data exchange standards, and to implement in MobilityDB import/export functions for the relevant ones. Examples for these standards are: |
| + | * GTFS static, https://developers.google.com/transit/gtfs/ | ||
| + | * GTFS realtime, https://developers.google.com/transit/gtfs-realtime/ | ||
| + | * NeTEx static, http://netex-cen.eu/ | ||
| + | * SIRI, http://www.transmodel-cen.eu/standards/siri/ | ||
| + | * More standards can be found on http://www.transmodel-cen.eu/category/standards/ | ||
| - | Toon Calders, Elisa Fromont, Baptiste Jeudy and Hoang Thanh Lam. | ||
| - | [[http://labh-curien.univ-st-etienne.fr/~fromont/|Analysis of Videos using Tile Mining.]]\\ | ||
| - | In: //ECML/PKDD Workshop on Real-World Challenges for Data Stream Mining//, Prague, 2013 | ||
| - | Interested? Contact [[toon.calders@ulb.ac.be|Toon Calders]] | ||
| + | **Interested?** | ||
| + | * Contact : [[ezimanyi@ulb.ac.be|Esteban Zimanyi]] | ||
| - | ===== Design and Implementation of a Curriculum Revision Tool ====== | + | **Status**: available |
| - | Stijn Vansummeren (WIT), Frédéric Robert (BEAMS) | + | =====Visualizing spatiotemporal data===== |
| + | Data visualization is essential for understanding and presenting it. starting with the temporal point, which is the database representation of a moving point object. Typically, it is visualized in a movie style, as a point that moves over a background map. The numerical attributes of this temporal point, such as the speed, are temporal floats. These can be visualized as function curves from the time t to the value v. | ||
| - | This MFE concers the analysis, design, and implementation of a | + | The goal of this thesis is to develop a visualization tool for the MobilityDB temporal types. The architecture of this tool should be innovative, so that it will be easy to extend it with more temporal types in the future. should be This tool should be integrated as an extension of a mainstream visualization software. A good candidate is QGIS (https://www.qgis.org/en/site/). The choice is however left open as part of the survey. |
| - | software system that can assist in the revision of teaching curricula | + | |
| - | (also known as teaching programs). | + | |
| - | The primary targetted functionalities of the software system are as | ||
| - | follows: | ||
| - | * It should allow to make different versions of the teaching programs, much in the same way as version control systems like GIT and subversion offer the possibility to make different "development branches" of a program's source code. | ||
| - | * It should allow an extensible means to check the modified program for inconsistentcies. (For example, if course X has course Y as prerequisite, then course Y should not be scheduled in 2nd semester and X in 1st semester. Moreover, the total number of ECTS of all courses should be at most 60 ECTS. ) | ||
| - | * It should allow to analyze the modifications proposed in the teaching programs, and summarize the impact that these changes could have on other programs. (For example, if a course is removed from the computer science curriculum, it should be flagged that it should also be removed from all curricula that included the course.) | ||
| - | * It should load data from (and preferably, save data to) the ULB central administration database. | ||
| - | * It should give suggestions concerning the impact of the modifications on the course schedules. | ||
| - | A proof-of-concept implementation of a revision tool that supports the first two requirements above is currently being developed in the context of a PROJH402 project. The MFE student that selects this topic is expected to: | + | **Interested?** |
| + | * Contact : [[ezimanyi@ulb.ac.be|Esteban Zimanyi]] | ||
| - | * Develop this prototype to a production-ready implementation. | + | **Status**: available |
| - | * Implement the communication with the central ULB database. | + | |
| - | * Implement the impact analysis concerning the course schedules. | + | |
| - | * Interact with the administration of the Ecole Polytechnique to fine-tune the above requirements; test the implementation; and integrate remarks after testing | + | |
| - | Contact : Stijn Vansummeren <stijn.vansummeren@ulb.ac.be>, Frédéric Robert <frrobert@ulb.ac.be> | + | =====Data modeling of spatiotemporal regions===== |
| + | In moving object databases, a lot of attention has been given to moving point objects. Many data model have been proposed for this. Less attention has been given to moving region objects. Imagine a herd of animals that moves together in the wild. At any time instant, this herd can be represented using a spatial region, e.g., their convex hull. Over time, this regions changes place and extent. A spatiotemporal region is an abstract data type that can represent this temporal evolution of the region. | ||
| - | ===== Design and Development of a Comprehensive DICOM validation application===== | + | This thesis is about proposing a data model for spatiotemporal regions, and implementing it in MobilityDB. This includes surveying the literature on moving object databases, and specifically on spatiotemporal reigons, proposing a discrete data model, implementing it, and implementing the basic data base functions and operations to make use of it. |
| - | Using the new XML machine-readable format of the DICOM standard (in the form of docbook documents), the architecture of software tools and services for the automatic extraction and utilization of the full content of the DICOM standard will be defined and the corresponding software solutions will be developed. A comprehensive DICOM validation application will also be developed as a pilot project using the previously created DICOM standard digital services. | ||
| - | References: <http://dicom.nema.org/; http://www.oasis-open.org/docbook/> | + | **Interested?** |
| - | Requirements: XML, XSL, database, Java or Python or C++. | + | * Contact : [[ezimanyi@ulb.ac.be|Esteban Zimanyi]] |
| - | Contacts : Arnaud Schenkel <arnaud.schenkel@ulb.ac.be>, David Wikler <david.wikler@ulb.ac.be>, Stijn Vansummeren <stijn.vansummeren@ulb.ac.be> | + | **Status**: available |
| - | ===== Structural compression of relational and semantic web databases ===== | + | |
| - | + | ||
| - | Stijn Vansummeren (WIT) | + | |
| - | + | ||
| - | Recent research in database management systems at ULB has shown how to | + | |
| - | theoretically construct succinct (compressed) representations for | + | |
| - | relational databases and semantic web databases. The advantage of | + | |
| - | these succinct representations is that they allow querying directly | + | |
| - | *on the succinct representation*, without needing to consult the | + | |
| - | underlying database. | + | |
| - | + | ||
| - | The goal of this thesis is to study scalable algorithms for | + | |
| - | constructing the actual succinct representations. Some in-memory | + | |
| - | algorithms are already known, but given the large size of typical | + | |
| - | database, distributed and out-of-memory alternatives need to be found. | + | |
| - | + | ||
| - | + | ||
| - | * Contact : [[stijn.vansummeren@ulb.ac.be|Stijn Vansummeren]] | + | |
| - | + | ||
| - | + | ||
| - | ===== A contribution to Apache DRILL ===== | + | |
| - | + | ||
| - | Google's research lab has produced a remarkable number of software | + | |
| - | systems for the analytics of Big Data: | + | |
| - | * [[|Map/Reduce]] for offline, batch-oriented data analysis over arbitrary datasets | + | |
| - | * [[http://googleresearch.blogspot.be/2009/06/large-scale-graph-computing-at-google.html|Pregel]] for offline analysis over graph-structured datasets | + | |
| - | * [[http://research.google.com/pubs/pub36632.html|Dremel]] for on-line analysis over structured datasets | + | |
| - | + | ||
| - | For Map/Reduce and Pregel, the Apache Software foundation has | + | |
| - | previously constructed open source implementations ([[http://hadoop.apache.org/|Hadoop]], | + | |
| - | [[https://giraph.apache.org/|Giraph]]). For Dremel, a project is | + | |
| - | currently underway to provide an Open Source implementation (known as | + | |
| - | [[http://incubator.apache.org/drill/index.html|Apache Drill]]). | + | |
| - | + | ||
| - | The goal of this thesis is to (1) study the current architecture of Apache | + | |
| - | Drill, (2) compare this with the state of the art in query processing | + | |
| - | for structured datasets; (3) contribute to the development of the | + | |
| - | Drill implementation. | + | |
| - | + | ||
| - | Students interested in this MFE are highly advised to follow the | + | |
| - | course {{http://cs.ulb.ac.be/public/teaching/infoh417|INFOH417 | + | |
| - | Database Systems Architecture}} for a background on query processing | + | |
| - | in traditional database management systems. | + | |
| - | + | ||
| - | * Contact : [[stijn.vansummeren@ulb.ac.be|Stijn Vansummeren]] | + | |
| - | ===== Aspects of Text Analytics and Information Extraction ===== | + | |
| - | + | ||
| - | Automatically extracting structured information from text is a task that has been pursued for decades. As a discipline, //Information Extraction// (IE) had its start with the [[http://acl.ldc.upenn.edu/C/C96/C96-1079.pdf|DARPA Message Understanding Conference in 1987]]. While early work in the area focused largely on military applications, recent changes have made information extraction increasingly important to an increasingly broad audience. Trends such as the rise of social media have produced huge amounts of text data, while analytics platforms like Hadoop have at the same time made the analysis of this data more accessible to a broad range of users. Since most analytics over text involves information extraction as a first step, IE is a very important part of | + | |
| - | data analysis in the enterprise today. | + | |
| - | + | ||
| - | Broadly speaking, there are two main schools of thought on the realization of IE: the //statistical// (machine-learning) methodology and the //rule-based// approach. The first started with simple models, then progressed to approaches based onprobabilistic graph models. Within the rule-based approach, most of the solutions build upon [[https://www.google.be/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&ved=0CEEQFjAB&url=http%3A%2F%2Fwww.dfki.de%2F~neumann%2Fesslli04%2Freader%2Foverview%2FIJCAI99.pdf&ei=1yZIUdSZPMWHPa2rgagP&usg=AFQjCNFA6QYIt4yNR0oZRL4yjd--kev37A&sig2=nEILF_cNDk4JWiVDS5BXvg&bvm=bv.43828540,d.ZWU|cascaded finite-state transducers]]. Most systems in both categories were built for academic settings, where most users are highly-trained computational linguists, where workloads cover only a small number of very well-defined tasks and data sets, and where extraction throughput is far less important than the accuracy of results. | + | |
| - | + | ||
| - | In practice, these existing tools suffer from a number of practical problems. For example, users need to have an intuitive understanding of machine learning or the ability to build and understand complex and highly interdependent rules. Determining why an extractor produced a given incorrect result | + | |
| - | is hence often deemed extremely difficult, which makes reuse of extractors across different data sets and applications impractical. And extremely | + | |
| - | high CPU and memory requirements made extractors cost-prohibitive to deploy over large-scale data sets. | + | |
| - | + | ||
| - | In 2005, researchers at the IBM Almaden Research Center started work on a new system specifically geared for practical information extraction in the enterprise. This effort lead to [[https://www.google.be/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&ved=0CEYQFjAB&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.179.356%26rep%3Drep1%26type%3Dpdf&ei=gyhIUe-XPIexPJ-fgLAG&usg=AFQjCNHgkbcREbd6bCA26BVf0FuIZ9n7Sg&sig2=LVQkus_67uSVlwK34BXZ8w&bvm=bv.43828540,d.ZWU|SystemT]] , a rule-based IE system with an SQL-like declarative language named [[http://pic.dhe.ibm.com/infocenter/bigins/v2r0/topic/com.ibm.swg.im.infosphere.biginsights.analyze.doc/doc/aql_overview.html|AQL (Annotation Query Language)]]. | + | |
| - | The declarative nature of AQL enables new kinds of tools for extractor | + | |
| - | development, and a cost-based optimizer for | + | |
| - | performance. | + | |
| - | + | ||
| - | The goal of this thesis is to study and compare both the | + | |
| - | traditional methods towards information extraction and the new | + | |
| - | AQL-based method proposed by SystemT, based on experimental | + | |
| - | evaluation of information extraction problems on the | + | |
| - | Web. Additional possible topics of study include the (1) | + | |
| - | implementation and optimization aspects of AQL, (2) the extension | + | |
| - | of AQL with probablistic methods, or (3) the inference of AQL | + | |
| - | rules from examples. | + | |
| - | + | ||
| - | + | ||
| - | Interested? Contact [[stijn.vansummeren@ulb.ac.be|Stijn Vansummeren]] | + | |
| - | + | ||
| - | ===== Models for programming Data Management in the Cloud ===== | + | |
| - | + | ||
| - | Many say that "The Cloud" is the next computing platform on the | + | |
| - | Web. Unfortunately, "the cloud" has become a marketing buzzword with | + | |
| - | many different services offered, from the rental of virtual machines, | + | |
| - | to the rental of storage space, to specific compute platforms | + | |
| - | (e.g. MapReduce) that offer transparent parallelization. | + | |
| - | + | ||
| - | In this thesis, we are interested in the cloud from the point of view | + | |
| - | of data management. There is a recent trend in data management | + | |
| - | research to use logic programming rule-based languages to specify | + | |
| - | distributed applications, most notably on the web, as well as | + | |
| - | inference in the semantic web (see below for a list of | + | |
| - | references). The goal of this thesis is to study, compare, and where | + | |
| - | possible extend the current (logic-programming based) proposals for | + | |
| - | managing data in the cloud. | + | |
| - | + | ||
| - | * References: | + | |
| - | * http://boom.cs.berkeley.edu/ | + | |
| - | * http://p2.cs.berkeley.edu/index.php | + | |
| - | * http://www.comlab.ox.ac.uk/files/3608/RR-10-21.pdf | + | |
| - | + | ||
| - | \\ | + | |
| - | * Contact : [[stijn.vansummeren@ulb.ac.be|Stijn Vansummeren]] | + | |
| - | * Status: **already taken** | + | |
| - | + | ||
| - | ===== Distributed Structural Indexes for RDF Data ===== | + | |
| - | + | ||
| - | In an effort to enable people to share information in a | + | |
| - | structured form on the Web as easily as they can share unstructured | + | |
| - | HTML documents today, the World Wide Web Consortium (W3C for short) is | + | |
| - | calling for the creation of a Web of Linked Data. In the same way as | + | |
| - | one uses HTML and hyperlinks to publish and connect information on the | + | |
| - | Web of Documents, one uses the RDF data model and RDF links to publish | + | |
| - | and connect structured information on the Web of Linked Data. The | + | |
| - | advantage of RDF over HTML lies in its simplicity: all information is | + | |
| - | represented uniformly as triples of the form (subject, predicate, | + | |
| - | object). This allows one to represent both facts about entities (e.g., | + | |
| - | (Tim Berners-Lee, age, 54)) and links between entities (e.g. (Tim | + | |
| - | Berners-Lee, author of, http://...)) in an easily | + | |
| - | machine-interpretable manner. This is much more difficult with HTML | + | |
| - | where there is little or no constraint on the way information is | + | |
| - | represented. | + | |
| - | + | ||
| - | Linked Data has the potential to turn the Web into one huge database | + | |
| - | with structured querying capabilities that vastly exceed the limited | + | |
| - | keyword search queries so common on the Web of Documents today. | + | |
| - | + | ||
| - | As a key component of efficient query answering in Linked Data Management systems, much research is focused on devising high-performance native RDF indexing data structures. One class of such indexes, called structural indexes, seem very promising in this respect. Currently however, structural indexes for RDF are difficult to distribute accross the web. Given the importance of distribution in web-scale data, the goal of this thesis is to investigate how structural RDF indexes can be used in a distributed query answering platform. | + | |
| - | + | ||
| - | + | ||
| - | * Contact : [[stijn.vansummeren@ulb.ac.be|Stijn Vansummeren]] | + | |
| - | + | ||
| - | + | ||
| - | + | ||
| - | + | ||
| - | =====Publishing and Using Spatio-temporal Data on the Semantic Web===== | + | |
| - | + | ||
| - | + | ||
| - | [[http://www.w3c.org/|RDF]] is the [[http://www.w3c.org/|W3C]] proposed framework for representing information | + | |
| - | in the Web. Basically, information in RDF is represented as a set of triples of the form (subject,predicate,object). RDF syntax is based on directed labeled graphs, where URIs are used as node labels and edge labels. The [[http://linkeddata.org/|Linked Open Data]] (LOD) initiative is aimed at extending the Web by means of publishing various open datasets as RDF, setting RDF links between data items from different data sources. Many companies and government agencies are moving towards publishing data following the LOD initiative. | + | |
| - | In order to do this, the original data must be transformed into Linked Open Data. Although most of these data are alphanumerical, most of the time they contained a spatial or spatio-temporal component, that must also be transformed. This can be exploited | + | |
| - | by application providers, that can build attractive and useful applications, in particular, for devices like mobile phones, tablets, etc. | + | |
| - | + | ||
| - | The goals of this thesis are: (1) study the existing proposals for mapping spatio-temporal data into LOD; (2) apply this mapping to a real-world case study (as was the case for the [[http://www.oscb.be/|Open Semantic Cloud for Brussels]] project; (3) Based on the produced mapping, and using existing applications like the [[http://linkedgeodata.org/|Linked Geo Data project]], build applications that make use of LOD for example, to find out which cultural events are taking place at a given time at a given location. | + | |
| - | + | ||
| - | + | ||
| - | * Contact: [[ezimanyi@ulb.ac.be|Esteban Zimányi]] | + | |
| - | + | ||
| - | =====Extending SPARQL for Spatio-temporal Data Support===== | + | |
| - | + | ||
| - | [[http://www.w3.org/TR/rdf-sparql-query/|SPARQL]] is the W3C standard language to query RDF data over the semantic web. Although syntactically similar to SQL, SPARQL is based on graph matching. In addition, SPARQL is aimed, basically, to query alphanumerical data. | + | |
| - | Therefore, a proposal to extend SPARQL to support spatial data, called [[http://www.opengeospatial.org/projects/groups/geosparqlswg/|GeoSPARQL]], has been presented to the Open Geospatial Consortium. | + | |
| - | + | ||
| - | In this thesis we propose to (1) perform an analysis of the current proposal for GeoSPARQL; (2) a study of current implementations of SPARQL that support spatial data; (3) implement simple extensions for SPARQL to support spatial data, and use these language in real-world use cases. | + | |
| - | + | ||
| - | + | ||
| - | * Contact: [[ezimanyi@ulb.ac.be|Esteban Zimányi]] | + | |
| - | + | ||