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teaching:mfe:is [2014/06/03 11:22]
svsummer [Master Thesis in Collaboration with DPI 24/7 Media Publishing]
teaching:mfe:is [2019/04/30 15:38]
ezimanyi [JDBC driver for Trajectories]
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-====== MFE 2014-2015 : Web and Information Systems ======+====== MFE 2019-2020 : Web and Information Systems ======
  
 ===== Introduction ===== ===== Introduction =====
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 ===== 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.
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   * 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.+===== Dynamic Query Processing on GPU Accelerators =====
  
-From a technical point of view you will : +This master thesis is put forward in the context ​of the DFAQ Research Project: "​Dyanmic Processing ​of Frequently Asked Queries",​ funded by the Wiener-Anspach foundation.
-  * 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)+
  
-Secondyou will analyze the different existing solutions ​for the orchestration ​of an elastic virtualization architecture.+Within this projectour lab is hence developing novel ways for processing "fast Big Data", i.e., processing of analytical queries where the underlying data is constantly being updated. The analytics problems envisioned cover wide areas of computer science and include database aggregate queries, probabilistic inference, matrix chain computation,​ and building statistical models.
  
-Technology used by the DPI 24/7 distribution : LinuxVarnish, NginX, Php-fpm, Mysql (in background TomcatSOLR).+The objective of this master thesis is to build upon the novel dynamic processing algorithms being developed in the laband complement these algorithms by proposing dynamic evaluation algorithms that execute on modern GPU architecturesthereby exploiting their massive parallel processing capabilities.
  
-Virtualization technology : Container virtualization and deployment with Dokku+Since our current development is done in the Scala programming language, prospective students should either know Scala, or being willing to learn it within the context of the master thesis.
  
-Interested? DIP 27/7 Contact [[ddu@audaxis.com|Dimitri Dujardin]]. Academic Supervisor [[svsummer@ulb.ac.be|Stijn Vansummeren]] 
  
-===== Automatic detection ​of name variations ===== +**Validation ​of the approach** Validation of master thesis'​ work should be done on two levels: 
-Toon Calders (WIT)+  * a theoretical level; by proposing and discussing alternative ways to do incremental computation on GPU architectures,​ and comparing these from a theoretical complexity viewpoint 
 +  * an experimental level; by proposing a benchmark collection of CEP queries that can be used to test the obtained versions of the interpreter/​compiler,​ and report on the experimentally observed performance on this benchmark.
  
-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:​ 
  
-^ Death certificate ^^ +**Deliverables** ​of the master thesis project 
-|Deceased |Johanna Louise Fredrika Frans | +  * An overview ​of query processing on GPUs 
-|Relation ​of the deceased |Gerard Cornelius Reincke de Sitter | +  * A definition ​of the analytics queries under consideration 
-|Father ​of the deceased |Carl Ludwig Frans | +  * A description ​of different possible dynamic evaluation algorithms for the analytical queries on GPU architectures. 
-|Mother ​of the deceased |Alida Philippina Zehender | +  * A theoretical comparison ​of these possibilities 
-|Type of deed |death certificate | +  * The implementaiton ​of the evaluation algorithm(s) (as an interpreter/​compiler) 
-|Number ​of deed |5 | +  * A benchmark set of queries and associated data sets for the experimental validation 
-|Place |Beers | +  * An experimental validation of the compiler, and analysis of the results.
-|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: ​ 
-  - 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 methodsBecause of the large size of the database it is very likely that most name variations occur frequentlyIn 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 :  [[svsummer@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]] 
  
-===== Analyzing state-of-the-art technology for handwritten text recognition in a practical case study ===== +**Status**: available
-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:+===== Multi-query Optimization ​in Spark =====
  
-[[https://dl.dropbox.com/​u/​5119252/​MFE/​069-50-3165-1813-00009.jpg]] \\  +Distributed computing platforms such as Hadoop and Spark focus on addressing the following challenges in large systems(1) latency, (2) scalability,​ and (3) fault toleranceDedicating computing resources for each application executed by Spark can lead to a waste of resourcesUnified distributed file systems such as Alluxio has provided a platform for computing results among simultaneously running applicationsHowever, it is up to the developers to decide on what to share.
-[[https://​dl.dropbox.com/​u/​5119252/​MFE/​069-50-3165-1815-00003.jpg]]+
  
-These two documents are scans of birth certificates (actually both are 2 birth certificates) from the Dutch city Grave. We have huge collection of such paper documents; about 3 millionof which several tens of thousands have been scanned. Furthermore,​ we have an index on these documents, created ​by volunteers. This index containsfor 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.+The objective ​of this master thesis is to optimize various applications running on Spark platformoptimize their execution plans by autonomously finding sharing opportunitiesnamely finding ​the RDDs that can be shared among these applications, and computing these shared plans once instead ​of multiple times for each query.
  
-Interested? Contact [[toon.calders@ulb.ac.be|Toon Calders]]+**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.
  
-===== Process Mining on Company Data for Detecting Security Breaches ===== +**Interested?​** Contact :  [[svsummer@ulb.ac.be|Stijn Vansummeren]]
-Toon Calders (WIT)+
  
-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. +**Status**available
-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.+===== Graph Indexing for Fast Subgraph Isomorphism Testing =====
  
 +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.
  
-Interested? Contact [[toon.calders@ulb.ac.be|Toon Calders]]+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.
  
-===== Mining patterns for compression ===== +**Interested?​** Contact : [[stijn.vansummeren@ulb.ac.be|Stijn Vansummeren]]
-Toon Calders (WIT)+
  
-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.  +**Status**available
-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]] 
  
-===== Pattern Mining ​for Object Tracking ​===== +=====Extending SPARQL ​for Spatio-temporal Data Support=====
-Toon Calders (WIT)+
  
-Pattern mining techniques are more and more often used in computer vision +[[http://​www.w3.org/​TR/​rdf-sparql-query/​|SPARQL]] is the W3C standard language ​to query RDF data over the semantic webAlthough syntactically similar to SQL,  SPARQL ​is based on graph matching. In additionSPARQL is aimedbasicallyto query alphanumerical data.   
-to obtain features that are more discriminative than those extracted +Thereforea 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.  ​ 
-using computer vision algorithmsThis is true for example in content-based +  
-images/​videos retrievalindexingclassificationtrackingetcHowever, the main +In this thesis we propose to (1perform an analysis ​of the current proposal ​for GeoSPARQL; (2) a study of  ​current implementations ​of SPARQL that support spatial ​data(3implement simple extensions for SPARQL to support spatial dataand use these language ​in real-world use cases 
-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 videosor 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-timeanalysis of videos and, in particular, for object tracking.+
  
-For more extensive information regarding the context and problem setting, see the following paper:+   * Contact[[ezimanyi@ulb.ac.be|Esteban Zimányi]]
  
-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]]+=====A Generic Similarity Measure For Symbolic Trajectories===== 
 +Moving object databases (MOD) are database systems that can store and manage moving object dataA moving object is a value that changes over timeIt 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. There are two types of MOD. The first is the trajectory database, that manages the history of movement. The second type, in contrast, manages the stream of current movement and the prediction of the near future. This thesis belongs to the first type (trajectory databases). The research in this area mainly goes around proposing data persistency models and query operations for trajectory data. 
  
 +A sub-topic of MOD is the study of semantic trajectories. It is motivated by the fact that the semantic of the movement is lost during the observation process. You GPS logger, for instance, would record a sequence of (lon, lat, time) that describe your trajectory. It won't, however, store the purpose of your trip (work, leisure, …), the transportation mode (car, bus, on foot, …), and other semantics of your trip. Research works have accordingly emerged to extract semantics from the trajectory raw data, and to provide database persistency to semantic trajectories. ​
  
-===== Design ​and Implementation ​of a Curriculum Revision Tool ======+Recently, Ralf Güting et al. published a model called “symbolic trajectories”,​ which can be viewed as a representation of semantic trajectories:​ 
 +Ralf Hartmut Güting, Fabio Valdés, ​and Maria Luisa Damiani. 2015. Symbolic Trajectories. ACM Trans. Spatial Algorithms Syst. 1, 2, Article 7 (July 2015), 51 pages. 
 +A symbolic trajectory is a very simple structure composed ​of a sequence of pairs (time interval, label). So, it is a time dependent label, where every label can tell something about the semantics of the moving object during its associated time interval. We think this model is promising because of its simplicity and genericness. ​  
  
-Stijn Vansummeren (WIT)Frédéric Robert (BEAMS)+The goal of this thesis is to implement a similarity operator for symbolic trajectories. There are three dimensions of similarity in symbolic trajectories:​ temporal similarityvalue similarity, and semantic similarity. Such an operator should be flexible to express arbitrary combinations of them. It should accept a pair of semantic trajectories and return a numerical value that can be used for clustering or ranking objects based on their similarity. Symbolic trajectories are similar to time series, except that labels are annotated by time intervals, rather than time points. We think that the techniques of time series similarity can be adopted for symbolic trajectories. This thesis should assess that, and implement a similarity measure based on time series similarity. The implementation is required to be done as an extension to PostGIS. We have already implemented some temporal types and operations on top of PostGIS, where you can start from. 
  
-This MFE concers ​the analysis, design, and implementation ​of a +  
-software system that can assist ​in the revision ​of teaching curricula +**Deliverables** of the master thesis project 
-(also known as teaching programs).+  * Reporting on the state of art of semantic trajectory similarity measures. 
 +  * Reporting on the state of art in time series similarity measures. 
 +  * Assessing ​the application ​of time series similarity to symbolic trajectories. 
 +  * Implementing symbolic trajectories on top of PostGIS. 
 +  * Implementation and evaluating the proposed symbolic trajectory similarity operator  ​
  
-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>​ 
  
-===== Design and Development of a Comprehensive DICOM validation application===== +=====JDBC driver for Trajectories===== 
 +The research in moving object databases MOD has been active since the early 2000. Many individual works have been proposed to deal with the different aspects of data modeling, indexing, operations, etc. 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.
  
-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.+In our group, we are in the course ​of building MobilityDBa 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 tfloatp 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 tfloatp builds on the PostgreSQL doubleprecision type, and the tgeompoint build on the PostGIS geometry(point) type. Similarly MobilityDB builds on existing operations, indexing, and optimization framework.
  
-References: <​http://​dicom.nema.org/; http://​www.oasis-open.org/​docbook/>​ +This is all made accessible via the SQL query interfaceCurrently MobilityDB is quite rich in terms of types and functionsIt can answer sophisticated queries in SQL.
-Requirements:​ XML, XSL, database, Java or Python or C++.+
  
-Contacts : Arnaud Schenkel <arnaud.schenkel@ulb.ac.be>David Wikler <​david.wikler@ulb.ac.be>, Stijn Vansummeren <stijn.vansummeren@ulb.ac.be> +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 dataThis thesis is about developing such a driverAs all other components of PostgreSQLits JDBC driver is also extensibleThis documentation gives a good explanation of the driver and the way it can be extended: 
-===== Structural compression of relational and semantic web databases =====+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
  
-Stijn Vansummeren (WIT)+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.  ​
  
-Recent research ​in database management systems at ULB has shown how to +This thesis project hence will help developing the student skills ​in: 
-theoretically construct succinct (compressed) representations for +  * Understanding the theory ​and the implementation of moving object ​databases. 
-relational databases ​and semantic web databases. ​The advantage of +  Understanding ​the architecture of extensible databasesin this case PostgreSQL. 
-these succinct representations is that they allow querying directly +  * Writing open source software.
-*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]] 
-  
 
teaching/mfe/is.txt · Last modified: 2020/09/29 17:03 by mahmsakr