Current Year

PhD
[1]
S. Dutta, “Efficient knowledge Management for Named Entities from Text,” Universität des Saarlandes, Saarbrücken, 2017.
Abstract
The evolution of search from keywords to entities has necessitated the efficient harvesting and management of entity-centric information for constructing knowledge bases catering to various applications such as semantic search, question answering, and information retrieval. The vast amounts of natural language texts available across diverse domains on the Web provide rich sources for discovering facts about named entities such as people, places, and organizations. A key challenge, in this regard, entails the need for precise identification and disambiguation of entities across documents for extraction of attributes/relations and their proper representation in knowledge bases. Additionally, the applicability of such repositories not only involves the quality and accuracy of the stored information, but also storage management and query processing efficiency. This dissertation aims to tackle the above problems by presenting efficient approaches for entity-centric knowledge acquisition from texts and its representation in knowledge repositories. This dissertation presents a robust approach for identifying text phrases pertaining to the same named entity across huge corpora, and their disambiguation to canonical entities present in a knowledge base, by using enriched semantic contexts and link validation encapsulated in a hierarchical clustering framework. This work further presents language and consistency features for classification models to compute the credibility of obtained textual facts, ensuring quality of the extracted information. Finally, an encoding algorithm, using frequent term detection and improved data locality, to represent entities for enhanced knowledge base storage and query performance is presented.
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BibTeX
@phdthesis{duttaphd17, TITLE = {Efficient knowledge Management for Named Entities from Text}, AUTHOR = {Dutta, Sourav}, LANGUAGE = {eng}, URL = {urn:nbn:de:bsz:291-scidok-67924}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, DATE = {2017}, ABSTRACT = {The evolution of search from keywords to entities has necessitated the efficient harvesting and management of entity-centric information for constructing knowledge bases catering to various applications such as semantic search, question answering, and information retrieval. The vast amounts of natural language texts available across diverse domains on the Web provide rich sources for discovering facts about named entities such as people, places, and organizations. A key challenge, in this regard, entails the need for precise identification and disambiguation of entities across documents for extraction of attributes/relations and their proper representation in knowledge bases. Additionally, the applicability of such repositories not only involves the quality and accuracy of the stored information, but also storage management and query processing efficiency. This dissertation aims to tackle the above problems by presenting efficient approaches for entity-centric knowledge acquisition from texts and its representation in knowledge repositories. This dissertation presents a robust approach for identifying text phrases pertaining to the same named entity across huge corpora, and their disambiguation to canonical entities present in a knowledge base, by using enriched semantic contexts and link validation encapsulated in a hierarchical clustering framework. This work further presents language and consistency features for classification models to compute the credibility of obtained textual facts, ensuring quality of the extracted information. Finally, an encoding algorithm, using frequent term detection and improved data locality, to represent entities for enhanced knowledge base storage and query performance is presented.}, }
Endnote
%0 Thesis %A Dutta, Sourav %Y Weikum, Gerhard %A referee: Nejdl, Wolfgang %A referee: Berberich, Klaus %+ Databases and Information Systems, MPI for Informatics, Max Planck Society International Max Planck Research School, MPI for Informatics, Max Planck Society Databases and Information Systems, MPI for Informatics, Max Planck Society External Organizations Databases and Information Systems, MPI for Informatics, Max Planck Society %T Efficient knowledge Management for Named Entities from Text : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-A793-E %U urn:nbn:de:bsz:291-scidok-67924 %I Universität des Saarlandes %C Saarbrücken %D 2017 %P xv, 134 p. %V phd %9 phd %X The evolution of search from keywords to entities has necessitated the efficient harvesting and management of entity-centric information for constructing knowledge bases catering to various applications such as semantic search, question answering, and information retrieval. The vast amounts of natural language texts available across diverse domains on the Web provide rich sources for discovering facts about named entities such as people, places, and organizations. A key challenge, in this regard, entails the need for precise identification and disambiguation of entities across documents for extraction of attributes/relations and their proper representation in knowledge bases. Additionally, the applicability of such repositories not only involves the quality and accuracy of the stored information, but also storage management and query processing efficiency. This dissertation aims to tackle the above problems by presenting efficient approaches for entity-centric knowledge acquisition from texts and its representation in knowledge repositories. This dissertation presents a robust approach for identifying text phrases pertaining to the same named entity across huge corpora, and their disambiguation to canonical entities present in a knowledge base, by using enriched semantic contexts and link validation encapsulated in a hierarchical clustering framework. This work further presents language and consistency features for classification models to compute the credibility of obtained textual facts, ensuring quality of the extracted information. Finally, an encoding algorithm, using frequent term detection and improved data locality, to represent entities for enhanced knowledge base storage and query performance is presented. %U http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=dehttp://scidok.sulb.uni-saarland.de/volltexte/2017/6792/
[2]
S. Gurajada, “Distributed Querying of Large Labeled Graphs,” Universität des Saarlandes, Saarbrücken, 2017.
Abstract
Graph is a vital abstract data type that has profound significance in several applications. Because of its versitality, graphs have been adapted into several different forms and one such adaption with many practical applications is the “Labeled Graph”, where vertices and edges are labeled. An enormous research effort has been invested in to the task of managing and querying graphs, yet a lot challenges are left unsolved. In this thesis, we advance the state-of-the-art for the following query models, and propose a distributed solution to process them in an efficient and scalable manner. • Set Reachability. We formalize and investigate a generalization of the basic notion of reachability, called set reachability. Set reachability deals with finding all reachable pairs for a given source and target sets. We present a non-iterative distributed solution that takes only a single round of communication for any set reachability query. This is achieved by precomputation, replication, and indexing of partial reachabilities among the boundary vertices. • Basic Graph Patterns (BGP). Supported by majority of query languages, BGP queries are a common mode of querying knowledge graphs, biological datasets, etc. We present a novel distributed architecture that relies on the concepts of asynchronous executions, join-ahead pruning, and a multi-threaded query processing framework to process BGP queries in an efficient and scalable manner. • Generalized Graph Patterns (GGP). These queries combine the semantics of pattern matching and navigational queries, and are popular in scenarios where the schema of an underlying graph is either unknown or partially known. We present a distributed solution with bimodal indexing layout that individually support efficient processing of BGP queries and navigational queries. Furthermore, we design a unified query optimizer and a processor to efficiently process GGP queries and also in a scalable manner. To this end, we propose a prototype distributed engine, coined “TriAD” (Triple Asynchronous and Distributed) that supports all the aforementioned query models. We also provide a detailed empirical evaluation of TriAD in comparison to several state-of-the-art systems over multiple real-world and synthetic datasets.
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BibTeX
@phdthesis{guraphd2017, TITLE = {Distributed Querying of Large Labeled Graphs}, AUTHOR = {Gurajada, Sairam}, LANGUAGE = {eng}, URL = {urn:nbn:de:bsz:291-scidok-67738}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, DATE = {2017}, ABSTRACT = {Graph is a vital abstract data type that has profound significance in several applications. Because of its versitality, graphs have been adapted into several different forms and one such adaption with many practical applications is the {\textquotedblleft}Labeled Graph{\textquotedblright}, where vertices and edges are labeled. An enormous research effort has been invested in to the task of managing and querying graphs, yet a lot challenges are left unsolved. In this thesis, we advance the state-of-the-art for the following query models, and propose a distributed solution to process them in an efficient and scalable manner. \mbox{$\bullet$} Set Reachability. We formalize and investigate a generalization of the basic notion of reachability, called set reachability. Set reachability deals with finding all reachable pairs for a given source and target sets. We present a non-iterative distributed solution that takes only a single round of communication for any set reachability query. This is achieved by precomputation, replication, and indexing of partial reachabilities among the boundary vertices. \mbox{$\bullet$} Basic Graph Patterns (BGP). Supported by majority of query languages, BGP queries are a common mode of querying knowledge graphs, biological datasets, etc. We present a novel distributed architecture that relies on the concepts of asynchronous executions, join-ahead pruning, and a multi-threaded query processing framework to process BGP queries in an efficient and scalable manner. \mbox{$\bullet$} Generalized Graph Patterns (GGP). These queries combine the semantics of pattern matching and navigational queries, and are popular in scenarios where the schema of an underlying graph is either unknown or partially known. We present a distributed solution with bimodal indexing layout that individually support efficient processing of BGP queries and navigational queries. Furthermore, we design a unified query optimizer and a processor to efficiently process GGP queries and also in a scalable manner. To this end, we propose a prototype distributed engine, coined {\textquotedblleft}TriAD{\textquotedblright} (Triple Asynchronous and Distributed) that supports all the aforementioned query models. We also provide a detailed empirical evaluation of TriAD in comparison to several state-of-the-art systems over multiple real-world and synthetic datasets.}, }
Endnote
%0 Thesis %A Gurajada, Sairam %Y Theobald, Martin %A referee: Weikum, Gerhard %A referee: Özsu, M. Tamer %A referee: Michel, Sebastian %+ Databases and Information Systems, MPI for Informatics, Max Planck Society International Max Planck Research School, MPI for Informatics, Max Planck Society Databases and Information Systems, MPI for Informatics, Max Planck Society Databases and Information Systems, MPI for Informatics, Max Planck Society External Organizations Databases and Information Systems, MPI for Informatics, Max Planck Society %T Distributed Querying of Large Labeled Graphs : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-8202-E %U urn:nbn:de:bsz:291-scidok-67738 %I Universität des Saarlandes %C Saarbrücken %D 2017 %P x, 167 p. %V phd %9 phd %X Graph is a vital abstract data type that has profound significance in several applications. Because of its versitality, graphs have been adapted into several different forms and one such adaption with many practical applications is the “Labeled Graph”, where vertices and edges are labeled. An enormous research effort has been invested in to the task of managing and querying graphs, yet a lot challenges are left unsolved. In this thesis, we advance the state-of-the-art for the following query models, and propose a distributed solution to process them in an efficient and scalable manner. • Set Reachability. We formalize and investigate a generalization of the basic notion of reachability, called set reachability. Set reachability deals with finding all reachable pairs for a given source and target sets. We present a non-iterative distributed solution that takes only a single round of communication for any set reachability query. This is achieved by precomputation, replication, and indexing of partial reachabilities among the boundary vertices. • Basic Graph Patterns (BGP). Supported by majority of query languages, BGP queries are a common mode of querying knowledge graphs, biological datasets, etc. We present a novel distributed architecture that relies on the concepts of asynchronous executions, join-ahead pruning, and a multi-threaded query processing framework to process BGP queries in an efficient and scalable manner. • Generalized Graph Patterns (GGP). These queries combine the semantics of pattern matching and navigational queries, and are popular in scenarios where the schema of an underlying graph is either unknown or partially known. We present a distributed solution with bimodal indexing layout that individually support efficient processing of BGP queries and navigational queries. Furthermore, we design a unified query optimizer and a processor to efficiently process GGP queries and also in a scalable manner. To this end, we propose a prototype distributed engine, coined “TriAD” (Triple Asynchronous and Distributed) that supports all the aforementioned query models. We also provide a detailed empirical evaluation of TriAD in comparison to several state-of-the-art systems over multiple real-world and synthetic datasets. %U http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=dehttp://scidok.sulb.uni-saarland.de/volltexte/2017/6773/
[3]
J. Kalojanov, “R-symmetry for Triangle Meshes: Detection and Applications,” Universität des Saarlandes, Saarbrücken, 2017.
Abstract
In this thesis, we investigate a certain type of local similarities between geometric shapes. We analyze the surface of a shape and find all points that are contained inside identical, spherical neighborhoods of a radius r. This allows us to decompose surfaces into canonical sets of building blocks, which we call microtiles. We show that the microtiles of a given object can be used to describe a complete family of related shapes. Each of these shapes is locally similar to the original, meaning that it contains identical r-neighborhoods, but can have completely different global structure. This allows for using r-microtiling for inverse modeling of shape variations and we develop a method for shape decomposi tion into rigid, 3D manufacturable building blocks that can be used to physically assemble shape collections. We obtain a small set of constructor pieces that are well suited for manufacturing and assembly by a novel method for tiling grammar simplification: We consider the connection between microtiles and noncontext-free tiling grammars and optimize a graph-based representation, finding a good balance between expressiveness, simplicity and ease of assembly. By changing the objective function, we can re-purpose the grammar simplification method for mesh compression. The microtiles of a model encode its geometrically redundant parts, which can be used for creating shape representations with minimal memory footprints. Altogether, with this work we attempt to give insights into how rigid partial symmetries can be efficiently computed and used in the context of inverse modeling of shape families, shape understanding, and compression.
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BibTeX
@phdthesis{Kalojanovphd2017, TITLE = {R-symmetry for Triangle Meshes: Detection and Applications}, AUTHOR = {Kalojanov, Javor}, LANGUAGE = {eng}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, DATE = {2017}, ABSTRACT = {In this thesis, we investigate a certain type of local similarities between geometric shapes. We analyze the surface of a shape and find all points that are contained inside identical, spherical neighborhoods of a radius r. This allows us to decompose surfaces into canonical sets of building blocks, which we call microtiles. We show that the microtiles of a given object can be used to describe a complete family of related shapes. Each of these shapes is locally similar to the original, meaning that it contains identical r-neighborhoods, but can have completely different global structure. This allows for using r-microtiling for inverse modeling of shape variations and we develop a method for shape decomposi tion into rigid, 3D manufacturable building blocks that can be used to physically assemble shape collections. We obtain a small set of constructor pieces that are well suited for manufacturing and assembly by a novel method for tiling grammar simplification: We consider the connection between microtiles and noncontext-free tiling grammars and optimize a graph-based representation, finding a good balance between expressiveness, simplicity and ease of assembly. By changing the objective function, we can re-purpose the grammar simplification method for mesh compression. The microtiles of a model encode its geometrically redundant parts, which can be used for creating shape representations with minimal memory footprints. Altogether, with this work we attempt to give insights into how rigid partial symmetries can be efficiently computed and used in the context of inverse modeling of shape families, shape understanding, and compression.}, }
Endnote
%0 Thesis %A Kalojanov, Javor %Y Slusallek, Philipp %A referee: Wand, Michael %A referee: Mitra, Niloy %+ International Max Planck Research School, MPI for Informatics, Max Planck Society External Organizations Computer Graphics, MPI for Informatics, Max Planck Society External Organizations %T R-symmetry for Triangle Meshes: Detection and Applications : %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-96A3-B %I Universität des Saarlandes %C Saarbrücken %D 2017 %P 94 p. %V phd %9 phd %X In this thesis, we investigate a certain type of local similarities between geometric shapes. We analyze the surface of a shape and find all points that are contained inside identical, spherical neighborhoods of a radius r. This allows us to decompose surfaces into canonical sets of building blocks, which we call microtiles. We show that the microtiles of a given object can be used to describe a complete family of related shapes. Each of these shapes is locally similar to the original, meaning that it contains identical r-neighborhoods, but can have completely different global structure. This allows for using r-microtiling for inverse modeling of shape variations and we develop a method for shape decomposi tion into rigid, 3D manufacturable building blocks that can be used to physically assemble shape collections. We obtain a small set of constructor pieces that are well suited for manufacturing and assembly by a novel method for tiling grammar simplification: We consider the connection between microtiles and noncontext-free tiling grammars and optimize a graph-based representation, finding a good balance between expressiveness, simplicity and ease of assembly. By changing the objective function, we can re-purpose the grammar simplification method for mesh compression. The microtiles of a model encode its geometrically redundant parts, which can be used for creating shape representations with minimal memory footprints. Altogether, with this work we attempt to give insights into how rigid partial symmetries can be efficiently computed and used in the context of inverse modeling of shape families, shape understanding, and compression. %U http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=dehttp://scidok.sulb.uni-saarland.de/volltexte/2017/6787/
[4]
X. Wu, “Structure-aware Content Creation,” Universität des Saarlandes, Saarbrücken, 2017.
Abstract
Nowadays, access to digital information has become ubiquitous, while three-dimensional visual representation is becoming indispensable to knowledge understanding and information retrieval. Three-dimensional digitization plays a natural role in bridging connections between the real and virtual world, which prompt the huge demand for massive three-dimensional digital content. But reducing the effort required for three-dimensional modeling has been a practical problem, and long standing challenge in compute graphics and related fields. In this thesis, we propose several techniques for lightening up the content creation process, which have the common theme of being structure-aware, \ie maintaining global relations among the parts of shape. We are especially interested in formulating our algorithms such that they make use of symmetry structures, because of their concise yet highly abstract principles are universally applicable to most regular patterns. We introduce our work from three different aspects in this thesis. First, we characterized spaces of symmetry preserving deformations, and developed a method to explore this space in real-time, which significantly simplified the generation of symmetry preserving shape variants. Second, we empirically studied three-dimensional offset statistics, and developed a fully automatic retargeting application, which is based on verified sparsity. Finally, we made step forward in solving the approximate three-dimensional partial symmetry detection problem, using a novel co-occurrence analysis method, which could serve as the foundation to high-level applications.
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BibTeX
@phdthesis{wuphd2017, TITLE = {Structure-aware Content Creation}, AUTHOR = {Wu, Xiaokun}, LANGUAGE = {eng}, URL = {urn:nbn:de:bsz:291-scidok-67750}, SCHOOL = {Universit{\"a}t des Saarlandes}, ADDRESS = {Saarbr{\"u}cken}, YEAR = {2017}, MARGINALMARK = {$\bullet$}, DATE = {2017}, ABSTRACT = {Nowadays, access to digital information has become ubiquitous, while three-dimensional visual representation is becoming indispensable to knowledge understanding and information retrieval. Three-dimensional digitization plays a natural role in bridging connections between the real and virtual world, which prompt the huge demand for massive three-dimensional digital content. But reducing the effort required for three-dimensional modeling has been a practical problem, and long standing challenge in compute graphics and related fields. In this thesis, we propose several techniques for lightening up the content creation process, which have the common theme of being structure-aware, \ie maintaining global relations among the parts of shape. We are especially interested in formulating our algorithms such that they make use of symmetry structures, because of their concise yet highly abstract principles are universally applicable to most regular patterns. We introduce our work from three different aspects in this thesis. First, we characterized spaces of symmetry preserving deformations, and developed a method to explore this space in real-time, which significantly simplified the generation of symmetry preserving shape variants. Second, we empirically studied three-dimensional offset statistics, and developed a fully automatic retargeting application, which is based on verified sparsity. Finally, we made step forward in solving the approximate three-dimensional partial symmetry detection problem, using a novel co-occurrence analysis method, which could serve as the foundation to high-level applications.}, }
Endnote
%0 Thesis %A Wu, Xiaokun %Y Seidel, Hans-Peter %A referee: Wand, Michael %A referee: Hildebrandt, Klaus %A referee: Klein, Reinhard %+ Computer Graphics, MPI for Informatics, Max Planck Society International Max Planck Research School, MPI for Informatics, Max Planck Society Computer Graphics, MPI for Informatics, Max Planck Society Computer Graphics, MPI for Informatics, Max Planck Society Computer Graphics, MPI for Informatics, Max Planck Society External Organizations %T Structure-aware Content Creation : Detection, Retargeting and Deformation %G eng %U http://hdl.handle.net/11858/00-001M-0000-002C-8072-6 %U urn:nbn:de:bsz:291-scidok-67750 %I Universität des Saarlandes %C Saarbrücken %D 2017 %P viii, 61 p. %V phd %9 phd %X Nowadays, access to digital information has become ubiquitous, while three-dimensional visual representation is becoming indispensable to knowledge understanding and information retrieval. Three-dimensional digitization plays a natural role in bridging connections between the real and virtual world, which prompt the huge demand for massive three-dimensional digital content. But reducing the effort required for three-dimensional modeling has been a practical problem, and long standing challenge in compute graphics and related fields. In this thesis, we propose several techniques for lightening up the content creation process, which have the common theme of being structure-aware, \ie maintaining global relations among the parts of shape. We are especially interested in formulating our algorithms such that they make use of symmetry structures, because of their concise yet highly abstract principles are universally applicable to most regular patterns. We introduce our work from three different aspects in this thesis. First, we characterized spaces of symmetry preserving deformations, and developed a method to explore this space in real-time, which significantly simplified the generation of symmetry preserving shape variants. Second, we empirically studied three-dimensional offset statistics, and developed a fully automatic retargeting application, which is based on verified sparsity. Finally, we made step forward in solving the approximate three-dimensional partial symmetry detection problem, using a novel co-occurrence analysis method, which could serve as the foundation to high-level applications. %U http://scidok.sulb.uni-saarland.de/volltexte/2017/6775/http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=de