Keyterm extraction from microblogs' messages using Wikipedia-based keyphraseness measure

The paper describes a method for keyterm extraction from messages of microblogs. The described approach utilizes the information obtained by the analysis of structure and content of Wikipedia. The algorithm is based on computation of “keyphraseness” measure for each term, i.e. an estimation of probability that it can be selected as a key in the text. The experimental study of the proposed technique demonstrated satisfactory results which significantly outpaces analogues. As a demonstration of possible application of the algorithm, the prototype of context-sensitive advertising system has been implemented. This system is able to obtain the descriptions of the goods relevant to the found keyterms from Amazon online store. Several suggestions are also made on how to utilize the information obtained by the analysis of Twitter messages in different auxiliary services.

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