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Abstract

Due to the large repository of documents available on the web, users are usually inundated by a large volume of information, most of which is found to be irrelevant. Since user perspectives vary, a client-side text filtering system that learns the user's perspective can reduce the problem of irrelevant retrieval. In this paper, we have provided the design of a customized text information filtering system which learns user preferences and modifies the initial query to fetch better documents. It uses a rough-fuzzy reasoning scheme. The rough-set based reasoning takes care of natural language nuances, like synonym handling, very elegantly. The fuzzy decider provides qualitative grading to the documents for the user's perusal. We have provided the detailed design of the various modules and some results related to the performance analysis of the system.

Source

Information processing and management. 41(2005) no.2, S.195-216

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Abstract

Finding similarity between concepts based on semantics has become a new trend in many applications (e.g., biomedical informatics, natural language processing). Measuring the Semantic Similarity (SS) with higher accuracy is a challenging task. In this context, the Information Content (IC)-based SS measure has gained popularity over the others. The notion of IC evolves from the science of information theory. Information theory has very high potential to characterize the semantics of concepts. Designing an IC-based SS framework comprises (i) an IC calculator, and (ii) an SS calculator. In this article, we propose a generic intrinsic IC-based SS calculator. We also introduce here a new structural aspect of an ontology called DCS (Disjoint Common Subsumers) that plays a significant role in deciding the similarity between two concepts. We evaluated our proposed similarity calculator with the existing intrinsic IC-based similarity calculators, as well as corpora-dependent similarity calculators using several benchmark data sets. The experimental results show that the proposed similarity calculator produces a high correlation with human evaluation over the existing state-of-the-art IC-based similarity calculators.

Source

Journal of the Association for Information Science and Technology. 69(2018) no.8, S.1023-1034

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

Presents Ranganathan's ideas on reference service and his division of the process into the following categories: initiation; general help to general modes; ready reference service; and long range reference service. Discusses the mechanism he developed for the analysis of reference service and refers to the stress he laid upon the humanistic side of reference service and its symbiotic relationship with the classification of knowledge. Argues that some of his ideas are still relevant although he was unable to foresee the revolution of reference service by information technology

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Source

CLIS observer. 9(1992) nos.1/2, S.16-22