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  1. Xiong, C.: Knowledge based text representations for information retrieval (2016) 0.30 
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    Abstract
    The successes of information retrieval (IR) in recent decades were built upon bag-of-words representations. Effective as it is, bag-of-words is only a shallow text understanding; there is a limited amount of information for document ranking in the word space. This dissertation goes beyond words and builds knowledge based text representations, which embed the external and carefully curated information from knowledge bases, and provide richer and structured evidence for more advanced information retrieval systems. This thesis research first builds query representations with entities associated with the query. Entities' descriptions are used by query expansion techniques that enrich the query with explanation terms. Then we present a general framework that represents a query with entities that appear in the query, are retrieved by the query, or frequently show up in the top retrieved documents. A latent space model is developed to jointly learn the connections from query to entities and the ranking of documents, modeling the external evidence from knowledge bases and internal ranking features cooperatively. To further improve the quality of relevant entities, a defining factor of our query representations, we introduce learning to rank to entity search and retrieve better entities from knowledge bases. In the document representation part, this thesis research also moves one step forward with a bag-of-entities model, in which documents are represented by their automatic entity annotations, and the ranking is performed in the entity space.
    This proposal includes plans to improve the quality of relevant entities with a co-learning framework that learns from both entity labels and document labels. We also plan to develop a hybrid ranking system that combines word based and entity based representations together with their uncertainties considered. At last, we plan to enrich the text representations with connections between entities. We propose several ways to infer entity graph representations for texts, and to rank documents using their structure representations. This dissertation overcomes the limitation of word based representations with external and carefully curated information from knowledge bases. We believe this thesis research is a solid start towards the new generation of intelligent, semantic, and structured information retrieval.
    Content
    Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.
  2. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.25 
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    Abstract
    By the explosion of possibilities for a ubiquitous content production, the information overload problem reaches the level of complexity which cannot be managed by traditional modelling approaches anymore. Due to their pure syntactical nature traditional information retrieval approaches did not succeed in treating content itself (i.e. its meaning, and not its representation). This leads to a very low usefulness of the results of a retrieval process for a user's task at hand. In the last ten years ontologies have been emerged from an interesting conceptualisation paradigm to a very promising (semantic) modelling technology, especially in the context of the Semantic Web. From the information retrieval point of view, ontologies enable a machine-understandable form of content description, such that the retrieval process can be driven by the meaning of the content. However, the very ambiguous nature of the retrieval process in which a user, due to the unfamiliarity with the underlying repository and/or query syntax, just approximates his information need in a query, implies a necessity to include the user in the retrieval process more actively in order to close the gap between the meaning of the content and the meaning of a user's query (i.e. his information need). This thesis lays foundation for such an ontology-based interactive retrieval process, in which the retrieval system interacts with a user in order to conceptually interpret the meaning of his query, whereas the underlying domain ontology drives the conceptualisation process. In that way the retrieval process evolves from a query evaluation process into a highly interactive cooperation between a user and the retrieval system, in which the system tries to anticipate the user's information need and to deliver the relevant content proactively. Moreover, the notion of content relevance for a user's query evolves from a content dependent artefact to the multidimensional context-dependent structure, strongly influenced by the user's preferences. This cooperation process is realized as the so-called Librarian Agent Query Refinement Process. In order to clarify the impact of an ontology on the retrieval process (regarding its complexity and quality), a set of methods and tools for different levels of content and query formalisation is developed, ranging from pure ontology-based inferencing to keyword-based querying in which semantics automatically emerges from the results. Our evaluation studies have shown that the possibilities to conceptualize a user's information need in the right manner and to interpret the retrieval results accordingly are key issues for realizing much more meaningful information retrieval systems.
    Content
    Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.
  3. Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019) 0.24 
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    Abstract
    On a scientific concept hierarchy, a parent concept may have a few attributes, each of which has multiple values being a group of child concepts. We call these attributes facets: classification has a few facets such as application (e.g., face recognition), model (e.g., svm, knn), and metric (e.g., precision). In this work, we aim at building faceted concept hierarchies from scientific literature. Hierarchy construction methods heavily rely on hypernym detection, however, the faceted relations are parent-to-child links but the hypernym relation is a multi-hop, i.e., ancestor-to-descendent link with a specific facet "type-of". We use information extraction techniques to find synonyms, sibling concepts, and ancestor-descendent relations from a data science corpus. And we propose a hierarchy growth algorithm to infer the parent-child links from the three types of relationships. It resolves conflicts by maintaining the acyclic structure of a hierarchy.
    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
  4. Information and communication technologies : international conference; proceedings / ICT 2010, Kochi, Kerala, India, September 7 - 9, 2010 (2010) 0.18 
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    Abstract
    This book constitutes the proceedings of the International Conference on Information and Communication Technologies held in Kochi, Kerala, India in September 2010.
    LCSH
    Information storage and retrieval systems
    Information systems
    RSWK
    Telekommunikationsnetz / Netzwerktopologie / Kongress / Cochin <Kerala, 2010>
    Informationstechnik / Kongress / Cochin <Kerala, 2010>
    Informatik / Kongress / Cochin <Kerala, 2010>
    Data Mining / Kongress / Cochin <Kerala, 2010>
    Series
    Communications in computer and information science; vol.101
    Subject
    Telekommunikationsnetz / Netzwerktopologie / Kongress / Cochin <Kerala, 2010>
    Informationstechnik / Kongress / Cochin <Kerala, 2010>
    Informatik / Kongress / Cochin <Kerala, 2010>
    Data Mining / Kongress / Cochin <Kerala, 2010>
    Information storage and retrieval systems
    Information systems
  5. ¬The Semantic Web : research and applications ; second European Semantic WebConference, ESWC 2005, Heraklion, Crete, Greece, May 29 - June 1, 2005 ; proceedings (2005) 0.16 
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    Abstract
    This book constitutes the refereed proceedings of the Second European Semantic Web Conference, ESWC 2005, heldin Heraklion, Crete, Greece in May/June 2005. The 48 revised full papers presented were carefully reviewed and selected from 148 submissions. The papers are organized in topical sections on semantic Web services, languages, ontologies, reasoning and querying, search and information retrieval, user and communities, natural language for the semantic Web, annotation tools, and semantic Web applications.
    LCSH
    Information storage and retrieval systems
    Information systems
    RSWK
    Semantic Web / Kongress / Iraklion <2005>
    Semantic Web / Ontologie <Wissensverarbeitung> / Kongress / Iraklion <2005>
    Subject
    Semantic Web / Kongress / Iraklion <2005>
    Semantic Web / Ontologie <Wissensverarbeitung> / Kongress / Iraklion <2005>
    Information storage and retrieval systems
    Information systems
  6. ¬The Semantic Web - ISWC 2010 : 9th International Semantic Web Conference, ISWC 2010, Shanghai, China, November 7-11, 2010, Revised Selected Papers, Part 2. (2010) 0.13 
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    Abstract
    The two-volume set LNCS 6496 and 6497 constitutes the refereed proceedings of the 9th International Semantic Web Conference, ISWC 2010, held in Shanghai, China, during November 7-11, 2010. Part I contains 51 papers out of 578 submissions to the research track. Part II contains 18 papers out of 66 submissions to the semantic Web in-use track, 6 papers out of 26 submissions to the doctoral consortium track, and also 4 invited talks. Each submitted paper were carefully reviewed. The International Semantic Web Conferences (ISWC) constitute the major international venue where the latest research results and technical innovations on all aspects of the Semantic Web are presented. ISWC brings together researchers, practitioners, and users from the areas of artificial intelligence, databases, social networks, distributed computing, Web engineering, information systems, natural language processing, soft computing, and human computer interaction to discuss the major challenges and proposed solutions, the success stories and failures, as well the visions that can advance research and drive innovation in the Semantic Web.
    Date
    29. 7.2011 14:44:56
    RSWK
    Semantic Web / Kongress / Schanghai <2010>
    Semantic Web / Ontologie <Wissensverarbeitung> / Kongress / Schanghai <2010>
    Semantic Web / Datenverwaltung / Wissensmanagement / Kongress / Schanghai <2010>
    Semantic Web / Anwendungssystem / Kongress / Schanghai <2010>
    Semantic Web / World Wide Web 2.0 / Kongress / Schanghai <2010>
    Subject
    Semantic Web / Kongress / Schanghai <2010>
    Semantic Web / Ontologie <Wissensverarbeitung> / Kongress / Schanghai <2010>
    Semantic Web / Datenverwaltung / Wissensmanagement / Kongress / Schanghai <2010>
    Semantic Web / Anwendungssystem / Kongress / Schanghai <2010>
    Semantic Web / World Wide Web 2.0 / Kongress / Schanghai <2010>
  7. ¬The Semantic Web - ISWC 2010 : 9th International Semantic Web Conference, ISWC 2010, Shanghai, China, November 7-11, 2010, Revised Selected Papers, Part I. (2010) 0.10 
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    Abstract
    The two-volume set LNCS 6496 and 6497 constitutes the refereed proceedings of the 9th International Semantic Web Conference, ISWC 2010, held in Shanghai, China, during November 7-11, 2010. Part I contains 51 papers out of 578 submissions to the research track. Part II contains 18 papers out of 66 submissions to the semantic Web in-use track, 6 papers out of 26 submissions to the doctoral consortium track, and also 4 invited talks. Each submitted paper were carefully reviewed. The International Semantic Web Conferences (ISWC) constitute the major international venue where the latest research results and technical innovations on all aspects of the Semantic Web are presented. ISWC brings together researchers, practitioners, and users from the areas of artificial intelligence, databases, social networks, distributed computing, Web engineering, information systems, natural language processing, soft computing, and human computer interaction to discuss the major challenges and proposed solutions, the success stories and failures, as well the visions that can advance research and drive innovation in the Semantic Web.
    Date
    29. 7.2011 14:44:56
    RSWK
    Semantic Web / Kongress / Schanghai <2010>
    Semantic Web / Ontologie <Wissensverarbeitung> / Kongress / Schanghai <2010>
    Semantic Web / Datenverwaltung / Wissensmanagement / Kongress / Schanghai <2010>
    Semantic Web / Anwendungssystem / Kongress / Schanghai <2010>
    Semantic Web / World Wide Web 2.0 / Kongress / Schanghai <2010>
    Subject
    Semantic Web / Kongress / Schanghai <2010>
    Semantic Web / Ontologie <Wissensverarbeitung> / Kongress / Schanghai <2010>
    Semantic Web / Datenverwaltung / Wissensmanagement / Kongress / Schanghai <2010>
    Semantic Web / Anwendungssystem / Kongress / Schanghai <2010>
    Semantic Web / World Wide Web 2.0 / Kongress / Schanghai <2010>
  8. Gödert, W.; Hubrich, J.; Nagelschmidt, M.: Semantic knowledge representation for information retrieval (2014) 0.04 
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    Abstract
    This book covers the basics of semantic web technologies and indexing languages, and describes their contribution to improve languages as a tool for subject queries and knowledge exploration. The book is relevant to information scientists, knowledge workers and indexers. It provides a suitable combination of theoretical foundations and practical applications.
    Content
    Introduction: envisioning semantic information spacesIndexing and knowledge organization -- Semantic technologies for knowledge representation -- Information retrieval and knowledge exploration -- Approaches to handle heterogeneity -- Problems with establishing semantic interoperability -- Formalization in indexing languages -- Typification of semantic relations -- Inferences in retrieval processes -- Semantic interoperability and inferences -- Remaining research questions.
    Date
    23. 7.2017 13:49:22
    LCSH
    Information retrieval
    Knowledge representation (Information theory)
    Information organization
    RSWK
    Information Retrieval
    Subject
    Information retrieval
    Knowledge representation (Information theory)
    Information organization
    Information Retrieval
  9. Rindflesch, T.C.; Aronson, A.R.: Semantic processing in information retrieval (1993) 0.04 
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    Abstract
    Intuition suggests that one way to enhance the information retrieval process would be the use of phrases to characterize the contents of text. A number of researchers, however, have noted that phrases alone do not improve retrieval effectiveness. In this paper we briefly review the use of phrases in information retrieval and then suggest extensions to this paradigm using semantic information. We claim that semantic processing, which can be viewed as expressing relations between the concepts represented by phrases, will in fact enhance retrieval effectiveness. The availability of the UMLS® domain model, which we exploit extensively, significantly contributes to the feasibility of this processing.
    Date
    29. 6.2015 14:51:28
  10. Mayfield, J.; Finin, T.: Information retrieval on the Semantic Web : integrating inference and retrieval 0.04 
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    Abstract
    One vision of the Semantic Web is that it will be much like the Web we know today, except that documents will be enriched by annotations in machine understandable markup. These annotations will provide metadata about the documents as well as machine interpretable statements capturing some of the meaning of document content. We discuss how the information retrieval paradigm might be recast in such an environment. We suggest that retrieval can be tightly bound to inference. Doing so makes today's Web search engines useful to Semantic Web inference engines, and causes improvements in either retrieval or inference to lead directly to improvements in the other.
    Date
    12. 2.2011 17:35:22
  11. Boteram, F.: Semantische Relationen in Dokumentationssprachen : vom Thesaurus zum semantischen Netz (2010) 0.04 
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    Abstract
    Moderne Verfahren des Information Retrieval verlangen nach aussagekräftigen und detailliert relationierten Dokumentationssprachen. Der selektive Transfer einzelner Modellierungsstrategien aus dem Bereich semantischer Technologien für die Gestaltung und Relationierung bestehender Dokumentationssprachen wird diskutiert. In Form einer Taxonomie wird ein hierarchisch strukturiertes Relationeninventar definiert, welches sowohl hinreichend allgemeine als auch zahlreiche spezifische Relationstypen enthält, die eine detaillierte und damit aussagekräftige Relationierung des Vokabulars ermöglichen. Das bringt einen Zugewinn an Übersichtlichkeit und Funktionalität. Im Gegensatz zu anderen Ansätzen und Überlegungen zur Schaffung von Relationeninventaren entwickelt der vorgestellte Vorschlag das Relationeninventar aus der Begriffsmenge eines bestehenden Gegenstandsbereichs heraus.
    Date
    2. 3.2013 12:29:05
    Source
    Wissensspeicher in digitalen Räumen: Nachhaltigkeit - Verfügbarkeit - semantische Interoperabilität. Proceedings der 11. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation, Konstanz, 20. bis 22. Februar 2008. Hrsg.: J. Sieglerschmidt u. H.P.Ohly
  12. Hüsken, P.: Informationssuche im Semantic Web : Methoden des Information Retrieval für die Wissensrepräsentation (2006) 0.03 
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    Abstract
    Das Semantic Web bezeichnet ein erweitertes World Wide Web (WWW), das die Bedeutung von präsentierten Inhalten in neuen standardisierten Sprachen wie RDF Schema und OWL modelliert. Diese Arbeit befasst sich mit dem Aspekt des Information Retrieval, d.h. es wird untersucht, in wie weit Methoden der Informationssuche sich auf modelliertes Wissen übertragen lassen. Die kennzeichnenden Merkmale von IR-Systemen wie vage Anfragen sowie die Unterstützung unsicheren Wissens werden im Kontext des Semantic Web behandelt. Im Fokus steht die Suche nach Fakten innerhalb einer Wissensdomäne, die entweder explizit modelliert sind oder implizit durch die Anwendung von Inferenz abgeleitet werden können. Aufbauend auf der an der Universität Duisburg-Essen entwickelten Retrievalmaschine PIRE wird die Anwendung unsicherer Inferenz mit probabilistischer Prädikatenlogik (pDatalog) implementiert.
    Date
    12. 2.2011 17:29:27
    Footnote
    Zugl.: Dortmund, Univ., Dipl.-Arb., 2006 u.d.T.: Hüsken, Peter: Information-Retrieval im Semantic-Web.
    RSWK
    Information Retrieval / Semantic Web
    Subject
    Information Retrieval / Semantic Web
  13. Atanassova, I.; Bertin, M.: Semantic facets for scientific information retrieval (2014) 0.03 
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    Abstract
    We present an Information Retrieval System for scientific publications that provides the possibility to filter results according to semantic facets. We use sentence-level semantic annotations that identify specific semantic relations in texts, such as methods, definitions, hypotheses, that correspond to common information needs related to scientific literature. The semantic annotations are obtained using a rule-based method that identifies linguistic clues organized into a linguistic ontology. The system is implemented using Solr Search Server and offers efficient search and navigation in scientific papers.
    Series
    Communications in computer and information science; vol.475
    Source
    Semantic Web Evaluation Challenge. SemWebEval 2014 at ESWC 2014, Anissaras, Crete, Greece, May 25-29, 2014, Revised Selected Papers. Eds.: V. Presutti et al
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  14. Developments in applied artificial intelligence : proceedings / 16th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2003, Loughborough, UK, June 23 - 26, 2003 (2003) 0.03 
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    RSWK
    Künstliche Intelligenz / Kongress / Loughborough <2003>
    Soft Computing / Kongress / Loughborough <2003>
    Expertensystem / Kongress / Loughborough <2003>
    Subject
    Künstliche Intelligenz / Kongress / Loughborough <2003>
    Soft Computing / Kongress / Loughborough <2003>
    Expertensystem / Kongress / Loughborough <2003>
  15. Beppler, F.D.; Fonseca, F.T.; Pacheco, R.C.S.: Hermeneus: an architecture for an ontology-enabled information retrieval (2008) 0.03 
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    Abstract
    Ontologies improve IR systems regarding its retrieval and presentation of information, which make the task of finding information more effective, efficient, and interactive. In this paper we argue that ontologies also greatly improve the engineering of such systems. We created a framework that uses ontology to drive the process of engineering an IR system. We developed a prototype that shows how a domain specialist without knowledge in the IR field can build an IR system with interactive components. The resulting system provides support for users not only to find their information needs but also to extend their state of knowledge. This way, our approach to ontology-enabled information retrieval addresses both the engineering aspect described here and also the usability aspect described elsewhere.
    Date
    28.11.2016 12:43:22
  16. Gödert, W.: Facets and typed relations as tools for reasoning processes in information retrieval (2014) 0.03 
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    Abstract
    Faceted arrangement of entities and typed relations for representing different associations between the entities are established tools in knowledge representation. In this paper, a proposal is being discussed combining both tools to draw inferences along relational paths. This approach may yield new benefit for information retrieval processes, especially when modeled for heterogeneous environments in the Semantic Web. Faceted arrangement can be used as a selection tool for the semantic knowledge modeled within the knowledge representation. Typed relations between the entities of different facets can be used as restrictions for selecting them across the facets.
    Series
    Communications in computer and information science; 478
    Source
    Metadata and semantics research: 8th Research Conference, MTSR 2014, Karlsruhe, Germany, November 27-29, 2014, Proceedings. Eds.: S. Closs et al
  17. Vallet, D.; Fernández, M.; Castells, P.: ¬An ontology-based information retrieval model (2005) 0.03 
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    Abstract
    Semantic search has been one of the motivations of the Semantic Web since it was envisioned. We propose a model for the exploitation of ontologybased KBs to improve search over large document repositories. Our approach includes an ontology-based scheme for the semi-automatic annotation of documents, and a retrieval system. The retrieval model is based on an adaptation of the classic vector-space model, including an annotation weighting algorithm, and a ranking algorithm. Semantic search is combined with keyword-based search to achieve tolerance to KB incompleteness. Our proposal is illustrated with sample experiments showing improvements with respect to keyword-based search, and providing ground for further research and discussion.
    Source
    The Semantic Web: research and applications ; second European Semantic WebConference, ESWC 2005, Heraklion, Crete, Greece, May 29 - June 1, 2005 ; proceedings. Eds.: A. Gómez-Pérez u. J. Euzenat
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  18. Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie : Ontologie-basiertes Information-Filtering und -Retrieval mit relationalen Datenbanken (2005) 0.03 
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    Date
    11. 2.2011 18:22:25
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  19. Calegari, S.; Sanchez, E.: Object-fuzzy concept network : an enrichment of ontologies in semantic information retrieval (2008) 0.02 
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    Abstract
    This article shows how a fuzzy ontology-based approach can improve semantic documents retrieval. After formally defining a fuzzy ontology and a fuzzy knowledge base, a special type of new fuzzy relationship called (semantic) correlation, which links the concepts or entities in a fuzzy ontology, is discussed. These correlations, first assigned by experts, are updated after querying or when a document has been inserted into a database. Moreover, in order to define a dynamic knowledge of a domain adapting itself to the context, it is shown how to handle a tradeoff between the correct definition of an object, taken in the ontology structure, and the actual meaning assigned by individuals. The notion of a fuzzy concept network is extended, incorporating database objects so that entities and documents can similarly be represented in the network. Information retrieval (IR) algorithm, using an object-fuzzy concept network (O-FCN), is introduced and described. This algorithm allows us to derive a unique path among the entities involved in the query to obtain maxima semantic associations in the knowledge domain. Finally, the study has been validated by querying a database using fuzzy recall, fuzzy precision, and coefficient variant measures in the crisp and fuzzy cases.
    Date
    9.11.2008 13:07:29
    Source
    Journal of the American Society for Information Science and Technology. 59(2008) no.13, S.2171-2185
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  20. Kiren, T.: ¬A clustering based indexing technique of modularized ontologies for information retrieval (2017) 0.02 
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    Abstract
    Indexing plays a vital role in Information Retrieval. With the availability of huge volume of information, it has become necessary to index the information in such a way to make easier for the end users to find the information they want efficiently and accurately. Keyword-based indexing uses words as indexing terms. It is not capable of capturing the implicit relation among terms or the semantics of the words in the document. To eliminate this limitation, ontology-based indexing came into existence, which allows semantic based indexing to solve complex and indirect user queries. Ontologies are used for document indexing which allows semantic based information retrieval. Existing ontologies or the ones constructed from scratch are used presently for indexing. Constructing ontologies from scratch is a labor-intensive task and requires extensive domain knowledge whereas use of an existing ontology may leave some important concepts in documents un-annotated. Using multiple ontologies can overcome the problem of missing out concepts to a great extent, but it is difficult to manage (changes in ontologies over time by their developers) multiple ontologies and ontology heterogeneity also arises due to ontologies constructed by different ontology developers. One possible solution to managing multiple ontologies and build from scratch is to use modular ontologies for indexing.
    Modular ontologies are built in modular manner by combining modules from multiple relevant ontologies. Ontology heterogeneity also arises during modular ontology construction because multiple ontologies are being dealt with, during this process. Ontologies need to be aligned before using them for modular ontology construction. The existing approaches for ontology alignment compare all the concepts of each ontology to be aligned, hence not optimized in terms of time and search space utilization. A new indexing technique is proposed based on modular ontology. An efficient ontology alignment technique is proposed to solve the heterogeneity problem during the construction of modular ontology. Results are satisfactory as Precision and Recall are improved by (8%) and (10%) respectively. The value of Pearsons Correlation Coefficient for degree of similarity, time, search space requirement, precision and recall are close to 1 which shows that the results are significant. Further research can be carried out for using modular ontology based indexing technique for Multimedia Information Retrieval and Bio-Medical information retrieval.
    Date
    20. 1.2015 18:30:22

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