Search (32 results, page 1 of 2)

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) 0.14

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Content: Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.

Conde, A.; Larrañaga, M.; Arruarte, A.; Elorriaga, J.A.; Roth, D.: litewi: a combined term extraction and entity linking method for eliciting educational ontologies from textbooks (2016) 0.03
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Abstract

Major efforts have been conducted on ontology learning, that is, semiautomatic processes for the construction of domain ontologies from diverse sources of information. In the past few years, a research trend has focused on the construction of educational ontologies, that is, ontologies to be used for educational purposes. The identification of the terminology is crucial to build ontologies. Term extraction techniques allow the identification of the domain-related terms from electronic resources. This paper presents LiTeWi, a novel method that combines current unsupervised term extraction approaches for creating educational ontologies for technology supported learning systems from electronic textbooks. LiTeWi uses Wikipedia as an additional information source. Wikipedia contains more than 30 million articles covering the terminology of nearly every domain in 288 languages, which makes it an appropriate generic corpus for term extraction. Furthermore, given that its content is available in several languages, it promotes both domain and language independence. LiTeWi is aimed at being used by teachers, who usually develop their didactic material from textbooks. To evaluate its performance, LiTeWi was tuned up using a textbook on object oriented programming and then tested with two textbooks of different domains-astronomy and molecular biology.

Date

22. 1.2016 12:38:14
Djioua, B.; Desclés, J.-P.; Alrahabi, M.: Searching and mining with semantic categories (2012) 0.03
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Abstract

A new model is proposed to retrieve information by building automatically a semantic metatext structure for texts that allow searching and extracting discourse and semantic information according to certain linguistic categorizations. This paper presents approaches for searching and mining full text with semantic categories. The model is built up from two engines: The first one, called EXCOM (Djioua et al., 2006; Alrahabi, 2010), is an automatic system for text annotation, related to discourse and semantic maps, which are specification of general linguistic ontologies founded on the Applicative and Cognitive Grammar. The annotation layer uses a linguistic method called Contextual Exploration, which handles the polysemic values of a term in texts. Several 'semantic maps' underlying 'point of views' for text mining guide this automatic annotation process. The second engine uses semantic annotated texts, produced previously in order to create a semantic inverted index, which is able to retrieve relevant documents for queries associated with discourse and semantic categories such as definition, quotation, causality, relations between concepts, etc. (Djioua & Desclés, 2007). This semantic indexation process builds a metatext layer for textual contents. Some data and linguistic rules sets as well as the general architecture that extend third-party software are expressed as supplementary information.

Footnote

Vgl.: http://www.igi-global.com/book/next-generation-search-engines/64423.

Source

Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a

Lassalle, E.; Lassalle, E.: Semantic models in information retrieval (2012) 0.02

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Footnote: Vgl.: http://www.igi-global.com/book/next-generation-search-engines/64424.
Source: Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a

Rajasurya, S.; Muralidharan, T.; Devi, S.; Swamynathan, S.: Semantic information retrieval using ontology in university domain (2012) 0.02
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Abstract

Today's conventional search engines hardly do provide the essential content relevant to the user's search query. This is because the context and semantics of the request made by the user is not analyzed to the full extent. So here the need for a semantic web search arises. SWS is upcoming in the area of web search which combines Natural Language Processing and Artificial Intelligence. The objective of the work done here is to design, develop and implement a semantic search engine- SIEU(Semantic Information Extraction in University Domain) confined to the university domain. SIEU uses ontology as a knowledge base for the information retrieval process. It is not just a mere keyword search. It is one layer above what Google or any other search engines retrieve by analyzing just the keywords. Here the query is analyzed both syntactically and semantically. The developed system retrieves the web results more relevant to the user query through keyword expansion. The results obtained here will be accurate enough to satisfy the request made by the user. The level of accuracy will be enhanced since the query is analyzed semantically. The system will be of great use to the developers and researchers who work on web. The Google results are re-ranked and optimized for providing the relevant links. For ranking an algorithm has been applied which fetches more apt results for the user query.
Bandholtz, T.; Schulte-Coerne, T.; Glaser, R.; Fock, J.; Keller, T.: iQvoc - open source SKOS(XL) maintenance and publishing tool (2010) 0.02
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Abstract

iQvoc is a new open source SKOS-XL vocabulary management tool developed by the Federal Environment Agency, Germany, and innoQ Deutschland GmbH. Its immediate purpose is maintaining and publishing reference vocabularies in the upcoming Linked Data cloud of environmental information, but it may be easily adapted to host any SKOS- XL compliant vocabulary. iQvoc is implemented as a Ruby on Rails application running on top of JRuby - the Java implementation of the Ruby Programming Language. To increase the user experience when editing content, iQvoc uses heavily the JavaScript library jQuery.
Saruladha, K.; Aghila, G.; Penchala, S.K.: Design of new indexing techniques based on ontology for information retrieval systems (2010) 0.02
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Abstract

Information Retrieval [IR] is the science of searching for documents, for information within documents, and for metadata about documents, as well as that of searching relational databases and the World Wide Web. This paper describes a document representation method instead of keywords ontological descriptors. The purpose of this paper is to propose a system for content-based querying of texts based on the availability of ontology for the concepts in the text domain and to develop new Indexing methods to improve RSV (Retrieval status value). There is a need for querying ontologies at various granularities to retrieve information from various sources to suit the requirements of Semantic web, to eradicate the mismatch between user request and response from the Information Retrieval system. Most of the search engines use indexes that are built at the syntactical level and return hits based on simple string comparisons. The indexes do not contain synonyms, cannot differentiate between homonyms and users receive different search results when they use different conjugation forms of the same word.
Allocca, C.; Aquin, M.d'; Motta, E.: Impact of using relationships between ontologies to enhance the ontology search results (2012) 0.02
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Abstract

Using semantic web search engines, such as Watson, Swoogle or Sindice, to find ontologies is a complex exploratory activity. It generally requires formulating multiple queries, browsing pages of results, and assessing the returned ontologies against each other to obtain a relevant and adequate subset of ontologies for the intended use. Our hypothesis is that at least some of the difficulties related to searching ontologies stem from the lack of structure in the search results, where ontologies that are implicitly related to each other are presented as disconnected and shown on different result pages. In earlier publications we presented a software framework, Kannel, which is able to automatically detect and make explicit relationships between ontologies in large ontology repositories. In this paper, we present a study that compares the use of the Watson ontology search engine with an extension,Watson+Kannel, which provides information regarding the various relationships occurring between the result ontologies. We evaluate Watson+Kannel by demonstrating through various indicators that explicit relationships between ontologies improve users' efficiency in ontology search, thus validating our hypothesis.
Wenige, L.; Ruhland, J.: Similarity-based knowledge graph queries for recommendation retrieval (2019) 0.02
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Abstract

Current retrieval and recommendation approaches rely on hard-wired data models. This hinders personalized cus-tomizations to meet information needs of users in a more flexible manner. Therefore, the paper investigates how similarity-basedretrieval strategies can be combined with graph queries to enable users or system providers to explore repositories in the LinkedOpen Data (LOD) cloud more thoroughly. For this purpose, we developed novel content-based recommendation approaches.They rely on concept annotations of Simple Knowledge Organization System (SKOS) vocabularies and a SPARQL-based querylanguage that facilitates advanced and personalized requests for openly available knowledge graphs. We have comprehensivelyevaluated the novel search strategies in several test cases and example application domains (i.e., travel search and multimediaretrieval). The results of the web-based online experiments showed that our approaches increase the recall and diversity of rec-ommendations or at least provide a competitive alternative strategy of resource access when conventional methods do not providehelpful suggestions. The findings may be of use for Linked Data-enabled recommender systems (LDRS) as well as for semanticsearch engines that can consume LOD resources. (PDF) Similarity-based knowledge graph queries for recommendation retrieval. Available from: https://www.researchgate.net/publication/333358714_Similarity-based_knowledge_graph_queries_for_recommendation_retrieval [accessed May 21 2020].
Wu, D.; Shi, J.: Classical music recording ontology used in a library catalog (2016) 0.01
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Abstract

In order to improve the organization of classical music information resources, we constructed a classical music recording ontology, on top of which we then designed an online classical music catalog. Our construction of the classical music recording ontology consisted of three steps: identifying the purpose, analyzing the ontology, and encoding the ontology. We identified the main classes and properties of the domain by investigating classical music recording resources and users' information needs. We implemented the ontology in the Web Ontology Language (OWL) using five steps: transforming the properties, encoding the transformed properties, defining ranges of the properties, constructing individuals, and standardizing the ontology. In constructing the online catalog, we first designed the structure and functions of the catalog based on investigations into users' information needs and information-seeking behaviors. Then we extracted classes and properties of the ontology using the Apache Jena application programming interface (API), and constructed a catalog in the Java environment. The catalog provides a hierarchical main page (built using the Functional Requirements for Bibliographic Records (FRBR) model), a classical music information network and integrated information service; this combination of features greatly eases the task of finding classical music recordings and more information about classical music.
Andreas, H.: On frames and theory-elements of structuralism (2014) 0.01
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Abstract

There are quite a few success stories illustrating philosophy's relevance to information science. One can cite, for example, Leibniz's work on a characteristica universalis and a corresponding calculus ratiocinator through which he aspired to reduce reasoning to calculating. It goes without saying that formal logic initiated research on decidability and computational complexity. But even beyond the realm of formal logic, philosophy has served as a source of inspiration for developments in information and computer science. At the end of the twentieth century, formal ontology emerged from a quest for a semantic foundation of information systems having a higher reusability than systems being available at the time. A success story that is less well documented is the advent of frame systems in computer science. Minsky is credited with having laid out the foundational ideas of such systems. There, the logic programming approach to knowledge representation is criticized by arguing that one should be more careful about the way human beings recognize objects and situations. Notably, the paper draws heavily on the writings of Kuhn and the Gestalt-theorists. It is not our intent, however, to document the traces of the frame idea in the works of philosophers. What follows is, rather, an exposition of a methodology for representing scientific knowledge that is essentially frame-like. This methodology is labelled as structuralist theory of science or, in short, as structuralism. The frame-like character of its basic meta-theoretical concepts makes structuralism likely to be useful in knowledge representation.
Sy, M.-F.; Ranwez, S.; Montmain, J.; Ragnault, A.; Crampes, M.; Ranwez, V.: User centered and ontology based information retrieval system for life sciences (2012) 0.01
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Abstract

Background: Because of the increasing number of electronic resources, designing efficient tools to retrieve and exploit them is a major challenge. Some improvements have been offered by semantic Web technologies and applications based on domain ontologies. In life science, for instance, the Gene Ontology is widely exploited in genomic applications and the Medical Subject Headings is the basis of biomedical publications indexation and information retrieval process proposed by PubMed. However current search engines suffer from two main drawbacks: there is limited user interaction with the list of retrieved resources and no explanation for their adequacy to the query is provided. Users may thus be confused by the selection and have no idea on how to adapt their queries so that the results match their expectations. Results: This paper describes an information retrieval system that relies on domain ontology to widen the set of relevant documents that is retrieved and that uses a graphical rendering of query results to favor user interactions. Semantic proximities between ontology concepts and aggregating models are used to assess documents adequacy with respect to a query. The selection of documents is displayed in a semantic map to provide graphical indications that make explicit to what extent they match the user's query; this man/machine interface favors a more interactive and iterative exploration of data corpus, by facilitating query concepts weighting and visual explanation. We illustrate the benefit of using this information retrieval system on two case studies one of which aiming at collecting human genes related to transcription factors involved in hemopoiesis pathway. Conclusions: The ontology based information retrieval system described in this paper (OBIRS) is freely available at: http://www.ontotoolkit.mines-ales.fr/ObirsClient/. This environment is a first step towards a user centred application in which the system enlightens relevant information to provide decision help.

Nielsen, M.: Neuronale Netze : Alpha Go - Computer lernen Intuition (2018) 0.01

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Source: Spektrum der Wissenschaft. 2018, H.1, S.22-27

Deokattey, S.; Neelameghan, A.; Kumar, V.: ¬A method for developing a domain ontology : a case study for a multidisciplinary subject (2010) 0.01

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Date: 22. 7.2010 19:41:16

Boteram, F.: Semantische Relationen in Dokumentationssprachen : vom Thesaurus zum semantischen Netz (2010) 0.01

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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

Madalli, D.P.; Balaji, B.P.; Sarangi, A.K.: Music domain analysis for building faceted ontological representation (2014) 0.01

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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

Hohmann, G.: ¬Die Anwendung des CIDOC-CRM für die semantische Wissensrepräsentation in den Kulturwissenschaften (2010) 0.00

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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

Semenova, E.: Ontologie als Begriffssystem : Theoretische Überlegungen und ihre praktische Umsetzung bei der Entwicklung einer Ontologie der Wissenschaftsdisziplinen (2010) 0.00

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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

Prud'hommeaux, E.; Gayo, E.: RDF ventures to boldly meet your most pedestrian needs (2015) 0.00

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Source: Bulletin of the Association for Information Science and Technology. 41(2015) no.4, S.18-22

Cui, H.: Competency evaluation of plant character ontologies against domain literature (2010) 0.00

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Date: 1. 6.2010 9:55:22

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