A Reputation Search Engine That Collects People's Opinions Using Information Extraction Technology

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In this paper, we propose a new search engine, "Reputation Search Engine (RSE)," that collects many kinds of opinions by using information extraction techniques. Although the Internet is one of the best mechanisms for acquiring and storing people's opinions, there is no appropriate tool to gather them. The RSE can collect opinions quickly and at a lower cost than conventional methods. To develop the RSE we first define the vague word "opinion" as a fact composed of three entities : "object name," "attribute expression" and "evaluative expression." This definition allows us to use an information extraction approach. We describe the RSE architecture, which divides the task of opinion extraction into two steps by exploiting a model that applies the above definition. The prototype RSE system utilizes two of the three entities, "object name" and "evaluative expression," to process opinions, and it implements the first step of the opinion extraction task. The system is based on a dictionary and patternmatching rules. The dictionary contains evaluative expressions, each of which has a label of positive or negative. This label information enables the system to classify extracted opinions into positive or negative types. The experimental results show the advantage of our opinion extraction method over an SVM text classification method in two representative domains on the Internet : computers and alcoholic beverages.
一般社団法人情報処理学会の論文
2004-06-15

A Reputation Search Engine That Collects People's Opinions Using Information Extraction Technology

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