Information extraction for personalised services based on conference alerts

Vandana Korde

International Journal of Data Mining, Modelling and Management, 2016, vol. 8, issue 1, 93-105

Abstract: Text mining is moderately new research area at the interaction of data mining, natural language processing (NLP), machine learning and information retrieval. The interconnected task, information extraction is a text transforming that places a specified set of significant items in a natural-language document. It distils organised data or knowledge from unstructured text by recognising references to named entities and additionally expressed relationships between such entities. We present a new schema for text mining as information extraction for prediction, which uses a learn information extraction system to transform text into more structures data which is then be further analysed or mine for discovering more general patterns and interesting relationships. This paper presents the work obtained by applying information extraction (IE) technique to a corpus of conference announcement posted on conference web newsgroups. The work is analysis of extracted essential name entities that were used to find the patterns of recent trends in research area and it also provide a platform to explore more on NLP aspects.

Keywords: data mining; text mining; web mining; information extraction; natural language processing; NLP; machine learning; information retrieval; nformation extraction for personalised services; personalisation; conference alerts; conference announcements; conference web newsgroups. (search for similar items in EconPapers)
Date: 2016
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