Semantic Information Retrieval based on Wikipedia Taxonomy
Authors | May Sabai Han |
|---|---|
Publication date | 2012 |
DOI | 10.7753/IJCATR0201.1016 |
Links | Original |
Semantic Information Retrieval based on Wikipedia Taxonomy - scientific work related to Wikipedia quality published in 2012, written by May Sabai Han.
Overview
Information retrieval is used to find a subset of relevant documents against a set of documents. Determining semantic similarity between two terms is a crucial problem in Web Mining for such applications as information retrieval systems and recommender systems. Semantic similarity refers to the sameness of two terms based on sameness of their meaning or their semantic contents. Recently many techniques have introduced measuring semantic similarity using Wikipedia, a free online encyclopedia. In this paper, a new technique of measuring semantic similarity is proposed. The proposed method uses Wikipedia as an ontology and spreading activation strategy to compute semantic similarity. The utility of the proposed system is evaluated by using the taxonomy of Wikipedia categories.
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Wikipedia Quality
Han, May Sabai. (2012). "[[Semantic Information Retrieval based on Wikipedia Taxonomy]]".DOI: 10.7753/IJCATR0201.1016.
English Wikipedia
{{cite journal |last1=Han |first1=May Sabai |title=Semantic Information Retrieval based on Wikipedia Taxonomy |date=2012 |doi=10.7753/IJCATR0201.1016 |url=https://wikipediaquality.com/wiki/Semantic_Information_Retrieval_based_on_Wikipedia_Taxonomy}}
HTML
Han, May Sabai. (2012). "<a href="https://wikipediaquality.com/wiki/Semantic_Information_Retrieval_based_on_Wikipedia_Taxonomy">Semantic Information Retrieval based on Wikipedia Taxonomy</a>".DOI: 10.7753/IJCATR0201.1016.
