-
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)
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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.
- Type
- a
-
Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005)
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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.
-
Schmitz-Esser, W.: Language of general communication and concept compatibility (1996)
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- Pages
- S.11-22
- Type
- a
-
Tudhope, D.; Hodge, G.: Terminology registries (2007)
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- Abstract
- A discussion on current initiatives regarding terminology registries.
- Date
- 26.12.2011 13:22:07
-
Nielsen, M.: Neuronale Netze : Alpha Go - Computer lernen Intuition (2018)
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- Source
- Spektrum der Wissenschaft. 2018, H.1, S.22-27
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- a
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Xiong, C.: Knowledge based text representations for information retrieval (2016)
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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.
-
Deokattey, S.; Neelameghan, A.; Kumar, V.: ¬A method for developing a domain ontology : a case study for a multidisciplinary subject (2010)
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- Abstract
- A method to develop a prototype domain ontology has been described. The domain selected for the study is Accelerator Driven Systems. This is a multidisciplinary and interdisciplinary subject comprising Nuclear Physics, Nuclear and Reactor Engineering, Reactor Fuels and Radioactive Waste Management. Since Accelerator Driven Systems is a vast topic, select areas in it were singled out for the study. Both qualitative and quantitative methods such as Content analysis, Facet analysis and Clustering were used, to develop the web-based model.
- Date
- 22. 7.2010 19:41:16
- Type
- a
-
Giunchiglia, F.; Villafiorita, A.; Walsh, T.: Theories of abstraction (1997)
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- Date
- 1.10.2018 14:13:22
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- a
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Börner, K.: Atlas of knowledge : anyone can map (2015)
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- Content
- One of a series of three publications influenced by the travelling exhibit Places & Spaces: Mapping Science, curated by the Cyberinfrastructure for Network Science Center at Indiana University. - Additional materials can be found at http://http://scimaps.org/atlas2. Erweitert durch: Börner, Katy. Atlas of Science: Visualizing What We Know.
- Date
- 22. 1.2017 16:54:03
22. 1.2017 17:10:56
-
Synak, M.; Dabrowski, M.; Kruk, S.R.: Semantic Web and ontologies (2009)
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- Date
- 31. 7.2010 16:58:22
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- a
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Hauff-Hartig, S.: Wissensrepräsentation durch RDF: Drei angewandte Forschungsbeispiele : Bitte recht vielfältig: Wie Wissensgraphen, Disco und FaBiO Struktur in Mangas und die Humanities bringen (2021)
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- Date
- 22. 5.2021 12:43:05
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Priss, U.: Faceted information representation (2000)
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- Abstract
- This paper presents an abstract formalization of the notion of "facets". Facets are relational structures of units, relations and other facets selected for a certain purpose. Facets can be used to structure large knowledge representation systems into a hierarchical arrangement of consistent and independent subsystems (facets) that facilitate flexibility and combinations of different viewpoints or aspects. This paper describes the basic notions, facet characteristics and construction mechanisms. It then explicates the theory in an example of a faceted information retrieval system (FaIR)
- Date
- 22. 1.2016 17:47:06
- Type
- a
-
Priss, U.: Faceted knowledge representation (1999)
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- Abstract
- Faceted Knowledge Representation provides a formalism for implementing knowledge systems. The basic notions of faceted knowledge representation are "unit", "relation", "facet" and "interpretation". Units are atomic elements and can be abstract elements or refer to external objects in an application. Relations are sequences or matrices of 0 and 1's (binary matrices). Facets are relational structures that combine units and relations. Each facet represents an aspect or viewpoint of a knowledge system. Interpretations are mappings that can be used to translate between different representations. This paper introduces the basic notions of faceted knowledge representation. The formalism is applied here to an abstract modeling of a faceted thesaurus as used in information retrieval.
- Date
- 22. 1.2016 17:30:31
- Type
- a
-
Madalli, D.P.; Balaji, B.P.; Sarangi, A.K.: Music domain analysis for building faceted ontological representation (2014)
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- Abstract
- This paper describes to construct faceted ontologies for domain modeling. Building upon the faceted theory of S.R. Ranganathan (1967), the paper intends to address the faceted classification approach applied to build domain ontologies. As classificatory ontologies are employed to represent the relationships of entities and objects on the web, the faceted approach helps to analyze domain representation in an effective way for modeling. Based on this perspective, an ontology of the music domain has been analyzed that would serve as a case study.
- Source
- Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
- Type
- a
-
Priss, U.: Description logic and faceted knowledge representation (1999)
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- Abstract
- The term "facet" was introduced into the field of library classification systems by Ranganathan in the 1930's [Ranganathan, 1962]. A facet is a viewpoint or aspect. In contrast to traditional classification systems, faceted systems are modular in that a domain is analyzed in terms of baseline facets which are then synthesized. In this paper, the term "facet" is used in a broader meaning. Facets can describe different aspects on the same level of abstraction or the same aspect on different levels of abstraction. The notion of facets is related to database views, multicontexts and conceptual scaling in formal concept analysis [Ganter and Wille, 1999], polymorphism in object-oriented design, aspect-oriented programming, views and contexts in description logic and semantic networks. This paper presents a definition of facets in terms of faceted knowledge representation that incorporates the traditional narrower notion of facets and potentially facilitates translation between different knowledge representation formalisms. A goal of this approach is a modular, machine-aided knowledge base design mechanism. A possible application is faceted thesaurus construction for information retrieval and data mining. Reasoning complexity depends on the size of the modules (facets). A more general analysis of complexity will be left for future research.
- Date
- 22. 1.2016 17:30:31
- Type
- a
-
Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie (2005)
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- Date
- 11. 2.2011 18:22:58
- Type
- a
-
Boteram, F.: Semantische Relationen in Dokumentationssprachen : vom Thesaurus zum semantischen Netz (2010)
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- 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
- Type
- a
-
Gendt, M. van; Isaac, I.; Meij, L. van der; Schlobach, S.: Semantic Web techniques for multiple views on heterogeneous collections : a case study (2006)
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- Abstract
- Integrated digital access to multiple collections is a prominent issue for many Cultural Heritage institutions. The metadata describing diverse collections must be interoperable, which requires aligning the controlled vocabularies that are used to annotate objects from these collections. In this paper, we present an experiment where we match the vocabularies of two collections by applying the Knowledge Representation techniques established in recent Semantic Web research. We discuss the steps that are required for such matching, namely formalising the initial resources using Semantic Web languages, and running ontology mapping tools on the resulting representations. In addition, we present a prototype that enables the user to browse the two collections using the obtained alignment while still providing her with the original vocabulary structures.
- Source
- Research and advanced technology for digital libraries : 10th European conference, proceedings / ECDL 2006, Alicante, Spain, September 17 - 22, 2006
- Type
- a
-
Renear, A.H.; Wickett, K.M.; Urban, R.J.; Dubin, D.; Shreeves, S.L.: Collection/item metadata relationships (2008)
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- Abstract
- Contemporary retrieval systems, which search across collections, usually ignore collection-level metadata. Alternative approaches, exploiting collection-level information, will require an understanding of the various kinds of relationships that can obtain between collection-level and item-level metadata. This paper outlines the problem and describes a project that is developing a logic-based framework for classifying collection/item metadata relationships. This framework will support (i) metadata specification developers defining metadata elements, (ii) metadata creators describing objects, and (iii) system designers implementing systems that take advantage of collection-level metadata. We present three examples of collection/item metadata relationship categories, attribute/value-propagation, value-propagation, and value-constraint and show that even in these simple cases a precise formulation requires modal notions in addition to first-order logic. These formulations are related to recent work in information retrieval and ontology evaluation.
- Source
- Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
- Type
- a
-
Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996)
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- Abstract
- We present a deductive data model for concept-based query expansion. It is based on three abstraction levels: the conceptual, linguistic and occurrence levels. Concepts and relationships among them are represented at the conceptual level. The expression level represents natural language expressions for concepts. Each expression has one or more matching models at the occurrence level. Each model specifies the matching of the expression in database indices built in varying ways. The data model supports a concept-based query expansion and formulation tool, the ExpansionTool, for environments providing heterogeneous IR systems. Expansion is controlled by adjustable matching reliability.
- Source
- Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR '96), Zürich, Switzerland, August 18-22, 1996. Eds.: H.P. Frei et al
- Type
- a
