Search (31 results, page 2 of 2)

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Abstract

The compilation of terminological vocabularies plays a central role in the organization and retrieval of scientific texts. Both simple keyword lists as well as sophisticated modellings of relationships between terminological concepts can make a most valuable contribution to the analysis, classification, and finding of appropriate digital documents, either on the Web or within local repositories. This seems especially true for long-established scientific fields with various theoretical and historical branches, such as linguistics, where the use of terminology within documents from different origins is sometimes far from being consistent. In this short paper, we report on the early stages of a project that aims at the re-design of an existing domain-specific KOS for grammatical content grammis. In particular, we deal with the terminological part of grammis and present the state-of-the-art of this online resource as well as the key re-design principles. Further, we propose questions regarding ramifications of the Linked Open Data and Semantic Web approaches for our re-design decisions.

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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].

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Abstract

Information exchange among many sources in Internet is more autonomous, dynamic and free. The situation drive difference view of concepts among sources. For example, word 'bank' has meaning as economic institution for economy domain, but for ecology domain it will be defined as slope of river or lake. In this paper, we will evaluate latent semantic and WordNet approach to calculate semantic similarity. The evaluation will be run for some concepts from different domain with reference by expert or human. Result of the evaluation can provide a contribution for mapping of concept, query rewriting, interoperability, etc.

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a

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Abstract

In this era of the Internet and distributed, multimedia computing, new and emerging classes of information systems applications have swept into the lives of office workers and people in general. From digital libraries, multimedia systems, geographic information systems, and collaborative computing to electronic commerce, virtual reality, and electronic video arts and games, these applications have created tremendous opportunities for information and computer science researchers and practitioners. As applications become more pervasive, pressing, and diverse, several well-known information retrieval (IR) problems have become even more urgent. Information overload, a result of the ease of information creation and transmission via the Internet and WWW, has become more troublesome (e.g., even stockbrokers and elementary school students, heavily exposed to various WWW search engines, are versed in such IR terminology as recall and precision). Significant variations in database formats and structures, the richness of information media (text, audio, and video), and an abundance of multilingual information content also have created severe information interoperability problems -- structural interoperability, media interoperability, and multilingual interoperability.

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Abstract

The JISC-funded HILT project is looking to make contact with staff in information services or projects interested in helping it test and refine its developing terminology services. The project is currently working to create pilot web services that will deliver machine-readable terminology and cross-terminology mappings data likely to be useful to information services wishing to extend or enhance the efficacy of their subject search or browse services. Based on SRW/U, SOAP, and SKOS, the HILT facilities, when fully operational, will permit such services to improve their own subject search and browse mechanisms by using HILT data in a fashion transparent to their users. On request, HILT will serve up machine-processable data on individual subject schemes (broader terms, narrower terms, hierarchy information, preferred and non-preferred terms, and so on) and interoperability data (usually intellectual or automated mappings between schemes, but the architecture allows for the use of other methods) - data that can be used to enhance user services. The project is also developing an associated toolkit that will help service technical staff to embed HILT-related functionality into their services. The primary aim is to serve JISC funded information services or services at JISC institutions, but information services outside the JISC domain may also find the proposed services useful and wish to participate in the test and refine process.

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