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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 8 of 8 1 CoTO: A Novel Approach for Fuzzy Aggregation of Semantic Similarity Measures ... Martinez, Jorge. - : figshare, 2018 BASE Show details 2 CoTO: A Novel Approach for Fuzzy Aggregation of Semantic Similarity Measures ... Martinez, Jorge. - : figshare, 2018 BASE Show details 3 An Overview of Textual Semantic Similarity Measures Based on Web Intelligence ... Martinez, Jorge. - : figshare, 2017 BASE Show details 4 CoTO: A Novel Approach for Fuzzy Aggregation of Semantic Similarity Measures ... Martinez, Jorge. - : figshare, 2017 BASE Show details 5 An Overview of Textual Semantic Similarity Measures Based on Web Intelligence ... Martinez, Jorge. - : figshare, 2017 BASE Show details 6 Semantic Similarity Measurement Using Historical Google Search Patterns ... Martinez, Jorge. - : figshare, 2017 BASE Show details 7 Semantic Similarity Measurement Using Historical Google Search Patterns ... Martinez, Jorge. - : figshare, 2017 Abstract: Computing the semantic similarity between terms (or short text expressions) that have the same meaning but which are not lexicographically similar is an important challenge in the information integration field. The problem is that techniques for textual semantic similarity measurement often fail to deal with words not covered by synonym dictionaries. In this paper, we try to solve this problem by determining the semantic similarity for terms using the knowledge inherent in the search history logs from the Google search engine. To do this, we have designed and evaluated four algorithmic methods for measuring the semantic similarity between terms using their associated history search patterns. These algorithmic methods are: a) frequent co-occurrence of terms in search patterns, b) computation of the relationship between search patterns, c) outlier coincidence on search patterns, and d) forecasting comparisons. We have shown experimentally that some of these methods correlate well with respect to human judgment ... Keyword: 80105 Expert Systems; 80107 Natural Language Processing; 80704 Information Retrieval and Web Search; FOS Computer and information sciences; FOS Media and communications URL: https://figshare.com/articles/preprint/Semantic_Similarity_Measurement_Using_Historical_Google_Search_Patterns/5624935 https://dx.doi.org/10.6084/m9.figshare.5624935 BASE Hide details 8 CoTO: A Novel Approach for Fuzzy Aggregation of Semantic Similarity Measures ... Martinez, Jorge. - : figshare, 2017 BASE Show details

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