Identifying and tracking online financial services through web mining and latent semantic indexing

Bernard, K.; Cassidy, Andrew; Clark, Monica; Liu, Kevin; Lobaton, Katrina; McNeill, Drew; Brown, Donald E.

doi:10.1109/sieds.2011.5876870

Cited by 4 publications

(1 citation statement)

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“…Latent Semantic Analysis (LSA) is one of the most promising tools used for finding patterns of relationships among a collection of documents (Bernard et al 2011). It is an indexing and retrieval method capable of identifying patterns of relationships between concepts, not just matching specific keywords.…”

Section: Keyword and Termmentioning

confidence: 99%

Managing corporate memory on the semantic web

Khilwani

Harding

2014

J Intell Manuf

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Corporate memory is the total body of data, information and knowledge required to deliver the strategic aims and objectives of an organization. In the current market, the rapidly increasing volume of unstructured documents in the enterprises has brought the challenge of building an autonomic framework to acquire, represent, learn and maintain corporate memory, and efficiently reason from it to aid in knowledge discovery and reuse. The concept of semantic web is being introduced in the enterprises to structure information in a machine readable way and enhance the understandability of the disparate information. Due to the continual popularity of the semantic web, this paper develops a framework for corporate memory management on the semantic web. The proposed approach gleans information from the documents, converts into a semantic web resource using RDF and RDF Schema and then identifies relations among them using Latent Semantic Analysis (LSA) technique. The efficacy of the proposed approach is demonstrated through empirical experiments conducted on two case studies.

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Section: Keyword and Termmentioning

confidence: 99%