The Experts below are selected from a list of 4188 Experts worldwide ranked by ideXlab platform
Hiroyuki Kitagawa - One of the best experts on this subject based on the ideXlab platform.
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extracting facets from textual contents for Faceted Search over xml data
Information Integration and Web-based Applications & Services, 2014Co-Authors: Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki KitagawaAbstract:Faceted Search for XML data is one of the promising exploration methods with high usability to find desired subtrees from a given XML data. This paper proposes improved approach of Faceted Search over XML data by utilizing facets containing unique and longer textual values, like titles of papers in bibliographic database. Our approach is to extract suitable terms which categorize the current results into several groups. Also we propose a task designing method for evaluating exploratory Search by defining specificity of tasks called specification level, and we introduce how to generate tasks with given specification level as well. With this task design, we evaluate our proposed approach and the results show our proposed approach improves Search performance comparing with the previous approaches, especially when tasks have low specification levels.
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iiWAS - Extracting Facets from Textual Contents for Faceted Search over XML Data
Proceedings of the 16th International Conference on Information Integration and Web-based Applications & Services - iiWAS '14, 2014Co-Authors: Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki KitagawaAbstract:Faceted Search for XML data is one of the promising exploration methods with high usability to find desired subtrees from a given XML data. This paper proposes improved approach of Faceted Search over XML data by utilizing facets containing unique and longer textual values, like titles of papers in bibliographic database. Our approach is to extract suitable terms which categorize the current results into several groups. Also we propose a task designing method for evaluating exploratory Search by defining specificity of tasks called specification level, and we introduce how to generate tasks with given specification level as well. With this task design, we evaluate our proposed approach and the results show our proposed approach improves Search performance comparing with the previous approaches, especially when tasks have low specification levels.
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a scheme of automated object and facet extraction for Faceted Search over xml data
International Database Engineering and Applications Symposium, 2014Co-Authors: Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki KitagawaAbstract:Applying Faceted Search for XML data enables users to Search XML data in an interactive manner. However, applying Faceted Search is challenging, because Faceted Search requires target subtrees (objects) and facets to be defined before-hand. To this problem, existing works assume that such objects and/or facets are defined manually, but it is infeasible to manually specify objects and facets in particular when the XML data are huge and/or its structure is quite complicated. To address this problem, this paper proposes an automatic extraction scheme of objects and facets from XML data. We propose two approaches, namely frequency-based approach and semantic-based approach, and also hybrid approach of them. The basic ideas of these approaches are that the frequently occurring XML elements seem to be objects and facets, and such XML elements may have semantically meaningful name. Although the proposed approaches are rather simple, the experiments using real world XML data show that the proposed approaches can automatically extract objects and facets from the XML data.
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IDEAS - A scheme of automated object and facet extraction for Faceted Search over XML data
Proceedings of the 18th International Database Engineering & Applications Symposium on - IDEAS '14, 2014Co-Authors: Takahiro Komamizu, Toshiyuki Amagasa, Hiroyuki KitagawaAbstract:Applying Faceted Search for XML data enables users to Search XML data in an interactive manner. However, applying Faceted Search is challenging, because Faceted Search requires target subtrees (objects) and facets to be defined before-hand. To this problem, existing works assume that such objects and/or facets are defined manually, but it is infeasible to manually specify objects and facets in particular when the XML data are huge and/or its structure is quite complicated. To address this problem, this paper proposes an automatic extraction scheme of objects and facets from XML data. We propose two approaches, namely frequency-based approach and semantic-based approach, and also hybrid approach of them. The basic ideas of these approaches are that the frequently occurring XML elements seem to be objects and facets, and such XML elements may have semantically meaningful name. Although the proposed approaches are rather simple, the experiments using real world XML data show that the proposed approaches can automatically extract objects and facets from the XML data.
Patrick Siehndel - One of the best experts on this subject based on the ideXlab platform.
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leveraging the semantics of tweets for adaptive Faceted Search on twitter
International Semantic Web Conference, 2011Co-Authors: Fabian Abel, Ilknur Celik, Geertjan Houben, Patrick SiehndelAbstract:In the last few years, Twitter has become a powerful tool for publishing and discussing information. Yet, content exploration in Twitter requires substantial effort. Users often have to scan information streams by hand. In this paper, we approach this problem by means of Faceted Search. We propose strategies for inferring facets and facet values on Twitter by enriching the semantics of individual Twitter messages (tweets) and present different methods, including personalized and context-adaptive methods, for making Faceted Search on Twitter more effective. We conduct a large-scale evaluation of Faceted Search strategies, show significant improvements over keyword Search and reveal significant benefits of those strategies that (i) further enrich the semantics of tweets by exploiting links posted in tweets, and that (ii) support users in selecting facet value pairs by adapting the Faceted Search interface to the specific needs and preferences of a user.
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International Semantic Web Conference (1) - Leveraging the semantics of tweets for adaptive Faceted Search on twitter
The Semantic Web – ISWC 2011, 2011Co-Authors: Fabian Abel, Ilknur Celik, Geertjan Houben, Patrick SiehndelAbstract:In the last few years, Twitter has become a powerful tool for publishing and discussing information. Yet, content exploration in Twitter requires substantial effort. Users often have to scan information streams by hand. In this paper, we approach this problem by means of Faceted Search. We propose strategies for inferring facets and facet values on Twitter by enriching the semantics of individual Twitter messages (tweets) and present different methods, including personalized and context-adaptive methods, for making Faceted Search on Twitter more effective. We conduct a large-scale evaluation of Faceted Search strategies, show significant improvements over keyword Search and reveal significant benefits of those strategies that (i) further enrich the semantics of tweets by exploiting links posted in tweets, and that (ii) support users in selecting facet value pairs by adapting the Faceted Search interface to the specific needs and preferences of a user.
Bernardo Cuenca Grau - One of the best experts on this subject based on the ideXlab platform.
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semfacet making hard Faceted Search easier
Conference on Information and Knowledge Management, 2017Co-Authors: Evgeny Kharlamov, Bernardo Cuenca Grau, Evgeny Sherkhonov, Egor V Kostylev, Luca Giacomelli, Ian HorrocksAbstract:Faceted Search is a prominent Search paradigm that became the standard in many Web applications and has also been recently proposed as a suitable paradigm for exploring and querying RDF graphs. One of the main challenges that hampers usability of Faceted Search systems especially in the RDF context is information overload, that is, when the size of Faceted interfaces becomes comparable to the size of the data over which the Search is performed. In this demo we present (an extension of) our Faceted Search system SemFacet and focus on features that address the information overload: ranking, aggregation, and reachability. The demo attendees will be able to try our system on an RDF graph that models online shopping over a catalogs with up to millions of products.
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CIKM - SemFacet: Making Hard Faceted Search Easier
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017Co-Authors: Evgeny Kharlamov, Bernardo Cuenca Grau, Evgeny Sherkhonov, Egor V Kostylev, Luca Giacomelli, Ian HorrocksAbstract:Faceted Search is a prominent Search paradigm that became the standard in many Web applications and has also been recently proposed as a suitable paradigm for exploring and querying RDF graphs. One of the main challenges that hampers usability of Faceted Search systems especially in the RDF context is information overload, that is, when the size of Faceted interfaces becomes comparable to the size of the data over which the Search is performed. In this demo we present (an extension of) our Faceted Search system SemFacet and focus on features that address the information overload: ranking, aggregation, and reachability. The demo attendees will be able to try our system on an RDF graph that models online shopping over a catalogs with up to millions of products.
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semantic Faceted Search with aggregation and recursion
International Semantic Web Conference, 2017Co-Authors: Evgeny Sherkhonov, Bernardo Cuenca Grau, Evgeny Kharlamov, Egor V KostylevAbstract:Faceted Search is the de facto approach for exploration of data in e-commerce: it allows users to construct queries in an intuitive way without a prior knowledge of formal query languages. This approach has been recently adapted to the context of RDF. Existing Faceted Search systems however do not allow users to construct queries with aggregation and recursion which poses limitations in practice. In this work we extend Faceted Search over RDF with these functionalities and study the corresponding query language. In particular, we investigate complexity of the query answering and query containment problems.
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International Semantic Web Conference (1) - Semantic Faceted Search with Aggregation and Recursion
Lecture Notes in Computer Science, 2017Co-Authors: Evgeny Sherkhonov, Bernardo Cuenca Grau, Evgeny Kharlamov, Egor V KostylevAbstract:Faceted Search is the de facto approach for exploration of data in e-commerce: it allows users to construct queries in an intuitive way without a prior knowledge of formal query languages. This approach has been recently adapted to the context of RDF. Existing Faceted Search systems however do not allow users to construct queries with aggregation and recursion which poses limitations in practice. In this work we extend Faceted Search over RDF with these functionalities and study the corresponding query language. In particular, we investigate complexity of the query answering and query containment problems.
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Faceted Search over ontology enhanced rdf data
Conference on Information and Knowledge Management, 2014Co-Authors: Marcelo Arenas, Bernardo Cuenca Grau, Evgeny Kharlamov, Sarunas Marciuska, Dmitriy ZheleznyakovAbstract:An increasing number of applications rely on RDF, OWL 2, and SPARQL for storing and querying data. SPARQL, however, is not targeted towards end-users, and suitable query interfaces are needed. Faceted Search is a prominent approach for end-user data access, and several RDF-based Faceted Search systems have been developed. There is, however, a lack of rigorous theoretical underpinning for Faceted Search in the context of RDF and OWL 2. In this paper, we provide such solid foundations. We formalise Faceted interfaces for this context, identify a fragment of first-order logic capturing the underlying queries, and study the complexity of answering such queries for RDF and OWL 2 profiles. We then study interface generation and update, and devise efficiently implementable algorithms. Finally, we have implemented and tested our Faceted Search algorithms for scalability, with encouraging results.
Dmitriy Zheleznyakov - One of the best experts on this subject based on the ideXlab platform.
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Faceted Search over RDF-based knowledge graphs
Journal of Web Semantics, 2016Co-Authors: Marcelo Arenas, Evgeny Kharlamov, Bernardo Cuenca Grau, Šarūnas Marciuška, Dmitriy ZheleznyakovAbstract:Knowledge graphs such as Yago and Freebase have become a powerful asset for enhancing Search, and are being intensively used in both academia in industry. Many existing knowledge graphs are either available as Linked Open Data, or they can be exported as RDF datasets enhanced with background knowledge in the form of an OWL 2 ontology. Faceted Search is the de facto approach for exploratory Search in many online applications, and has been recently proposed as a suitable paradigm for querying RDF repositories. In this paper, we provide rigorous theoretical underpinnings for Faceted Search in the context of RDFbased knowledge graphs enhanced with OWL 2 ontologies. We identify well-defined fragments of SPARQL that can be naturally captured using Faceted Search as a query paradigm, and establish the computational complexity of answering such queries. We also study the problem of updating Faceted interfaces, which is critical for guiding users in the formulation of meaningful queries during exploratory Search. We have implemented our approach in a fully-fledged Faceted Search system, SemFacet, which we have evaluated over the Yago knowledge graph
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Faceted Search over ontology enhanced rdf data
Conference on Information and Knowledge Management, 2014Co-Authors: Marcelo Arenas, Bernardo Cuenca Grau, Evgeny Kharlamov, Sarunas Marciuska, Dmitriy ZheleznyakovAbstract:An increasing number of applications rely on RDF, OWL 2, and SPARQL for storing and querying data. SPARQL, however, is not targeted towards end-users, and suitable query interfaces are needed. Faceted Search is a prominent approach for end-user data access, and several RDF-based Faceted Search systems have been developed. There is, however, a lack of rigorous theoretical underpinning for Faceted Search in the context of RDF and OWL 2. In this paper, we provide such solid foundations. We formalise Faceted interfaces for this context, identify a fragment of first-order logic capturing the underlying queries, and study the complexity of answering such queries for RDF and OWL 2 profiles. We then study interface generation and update, and devise efficiently implementable algorithms. Finally, we have implemented and tested our Faceted Search algorithms for scalability, with encouraging results.
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CIKM - Faceted Search over Ontology-Enhanced RDF Data
Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management - CIKM '14, 2014Co-Authors: Marcelo Arenas, Bernardo Cuenca Grau, Evgeny Kharlamov, Sarunas Marciuska, Dmitriy ZheleznyakovAbstract:An increasing number of applications rely on RDF, OWL 2, and SPARQL for storing and querying data. SPARQL, however, is not targeted towards end-users, and suitable query interfaces are needed. Faceted Search is a prominent approach for end-user data access, and several RDF-based Faceted Search systems have been developed. There is, however, a lack of rigorous theoretical underpinning for Faceted Search in the context of RDF and OWL 2. In this paper, we provide such solid foundations. We formalise Faceted interfaces for this context, identify a fragment of first-order logic capturing the underlying queries, and study the complexity of answering such queries for RDF and OWL 2 profiles. We then study interface generation and update, and devise efficiently implementable algorithms. Finally, we have implemented and tested our Faceted Search algorithms for scalability, with encouraging results.
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semfacet semantic Faceted Search over yago
The Web Conference, 2014Co-Authors: Marcelo Arenas, Bernardo Cuenca Grau, Evgeny Kharlamov, Sarunas Marciuska, Dmitriy Zheleznyakov, Ernesto JimenezruizAbstract:In this paper we demonstrate a system SemFacet, that is a proof of concept prototype for our semantic Faceted Search approach. SemFacet is implemented on top of the Yago knowledge base, powered by the OWL 2 RL triple store RDFox, and the full text Search engine Lucene. SemFacet has provided very encouraging results. Via logical reasoning SemFacet can automatically (i) extract facets, (ii) update the Faceted query interface with facets relevant for the current stage of the users query construction's session. SemFacet supports Faceted queries that are much more expressive than the ones of traditional Faceted Search applications; in particular SemFacet allows to (i) relate several collections of documents, and (ii) change the focus of queries (and, thus, SemFacet provides control over the documents in the query output to be displayed on the screen). Our approach is fully declarative: the same backend implementation can be used to power Faceted Search over any application, provided that metadata and knowledge are represented in RDF and OWL 2.
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towards semantic Faceted Search
The Web Conference, 2014Co-Authors: Marcelo Arenas, Bernardo Cuenca Grau, Sarunas Marciuska, Evgeny Evgeny, Dmitriy ZheleznyakovAbstract:In this paper we present limitations of conventional Faceted Search in the way data, facets, and queries are modelled. We discuss how these limitations can be addressed with Semantic Web technologies such as RDF, OWL 2, and SPARQL 1.1. We also present a system, SemFacet, that is a proof-of-concept prototype of our approach implemented on top of Yago knowledge base, powered by the OWL 2 RL triple store RDFox, and the full text Search engine Lucene.
Yannis Tzitzikas - One of the best experts on this subject based on the ideXlab platform.
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MTSR - Extending Faceted Search with Automated Object Ranking
Metadata and Semantic Research, 2019Co-Authors: Kostas Manioudakis, Yannis TzitzikasAbstract:Faceted Search is a widely used interaction scheme in digital libraries, e-commerce, and recently also in Linked Data. Nevertheless, object ranking in the context of Faceted Search is not well studied. In this paper we propose an extended version of the model enriched with parameters that enable specifying the characteristics of the sought object ranking. Then we provide an algorithm for producing an object ranking that satisfies these parameters. For doing so various sources are exploited including preferences and statistical properties of the dataset. Finally we present an implementation of the model, the GUI extensions that were required, as well as simulation-based evaluation results that provide evidence about the reduction of the user’s cost.
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Preference-Enriched Faceted Search for Voting Aid Applications
IEEE Transactions on Emerging Topics in Computing, 2019Co-Authors: Yannis Tzitzikas, Eleftherios DimitrakisAbstract:Most Voting Advice Applications (VAAs) are questionnaire-based systems. In this paper we introduce, analyze and evaluate an alternative approach; we show how Preference-enriched Faceted Search (PFS) can be used as a VAA. The introduced approach is more expressive, since it allows users to prioritize their preferences, it is more transparent since users can see how each preference affects the ranking of the parties, and it is more informative since during the interaction they can see the options associated to each party. Moreover we introduce an enrichment of PFS with scores that quantify the degree up to which a party satisfies the preferences of a user. Finally we compare the PFS with the questionnaire-based method according to various criteria, and we describe two task-based evaluations with users that we have carried out whose results were very positive.
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pfsgeo preference enriched Faceted Search for geographical data
OTM Confederated International Conferences "On the Move to Meaningful Internet Systems", 2017Co-Authors: Panagiotis Lionakis, Yannis TzitzikasAbstract:In this paper we show how an exploratory Search process, specifically the Preference-enriched Faceted Search (PFS) process, can be enriched for exploring datasets that also contain geographic information. In the introduced extension, that we call PFSgeo, the objects can have geographical coordinates, the interaction model is extended, and the web-interface is enriched with a map which the user can use for inspecting and restricting his focus, as well as for expressing preferences. Preference inheritance is supported as well as an automatic scope-based resolution of conflicts. We detail the implementation of the interaction model, elaborate on performance and report the positive results of a task-based evaluation with users. The value of PFSgeo is that it provides a generic and interactive method for aiding users to select the desired option(s) among a set of options that are described by several attributes including geographical ones, and it is the first model that supports map-based preferences.
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Using preference-enriched Faceted Search for species identification
International Journal of Metadata Semantics and Ontologies, 2016Co-Authors: Yannis Tzitzikas, Nicolas Bailly, Panagiotis Papadakos, Nikos Minadakis, George NikitakisAbstract:Species identification is essentially a decision-making process comprising steps in which the user makes a selection of characters, figures or photographs, or provides an input, that restricts other choices, until reaching one species. In some identification methods such decisions should have a specific order. Consequently, a wrong decision at the beginning of the process, could exclude a big set of options. To make this process more flexible and less vulnerable to wrong decisions, in this paper we investigate how a Preference-enriched Faceted Search PFS process can be used to aid the identification of species. We show how the proposed process covers and advances the existing methods and we report our experience from applying this process over data taken from FishBase. In the sequent, we elaborate on evaluation and we report the results of a task-based evaluation that shows that the PFS-based method can be used effectively by casual users.
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MTSR - Species Identification Through Preference-Enriched Faceted Search
Communications in Computer and Information Science, 2015Co-Authors: Yannis Tzitzikas, Nicolas Bailly, Panagiotis Papadakos, Nikos Minadakis, George NikitakisAbstract:There are various ways and corresponding tools that the marine biologist community uses for identifying one species. Species identification is essentially a decision making process comprising steps in which the user makes a selection of characters, figures or photographs, or provides an input that restricts other choices, and so on, until reaching one species. In many cases such decisions should have a specific order, as in the textual dichotomous identification keys. Consequently, if a wrong decision is made at the beginning of the process, it could exclude a big list of options. To make this process more flexible (i.e. independent of the order of selections) and less vulnerable to wrong decisions, in this paper we investigate how an exploratory Search process, specifically a Preference-enriched Faceted Search (PFS) process, can be used to aid the identification of species. We show how the proposed process covers and advances the existing methods. Finally, we report our experience from applying this process over data taken from FishBase, the most popular source for marine resources. The proposed approach can be applied over any kind of objects described by a number of attributes.
