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This paper investigates the semantic search performance of search engines. Initially, three keyword-based search engines (Google, Yahoo and Msn) and a semantic search engine (Hakia) were selected. Then, ten queries, from various topics, and four phrases, having different syntax but similar meanings, were determined.  After each query was run on(More)
In this article, the impact of increasing number of query words on information retrieval effectiveness of image search engines is investigated. First of all, four popular search engines, namely Google, Yahoo, Msn, and Ask are selected. Then, forty queries are extracted from the list of Wordtracker and categorized in four groups as one-word, two-word,(More)
In this paper, we evaluate the effectiveness of a new stemming algorithm , FINDSTEM, for use with Turkish documents and queries, and compare the use of this algorithm with the other two previously defined Turkish stem-mers, namely " A-F " and " L-M " algorithms. Of them, the FINDSTEM and A-F algorithms employ inflectional and derivational stemmers, whereas(More)
This is an investigation of information retrieval performance of Turk-ish search engines with respect to precision, normalized recall, coverage and novelty ratios. We defined seventeen query topics for Arabul, Arama, Netbul and Superonline. These queries were carefully selected to assess the capability of a search engine for handling broad or narrow topic(More)
This article investigates the information retrieval performance of popular search engines on finding Turkish documents. First of all, five popular search engines (Google, Yahoo, Msn, All the Web and Ask) and a list of Turkish queries are determined. Each query is run on each search engine one by one and first twenty documents on each retrieval output are(More)
This paper investigates the retrieval performance and necessity of major meta-image search engines (MISEs). Our study is realized in two phases. In the first phase, major image search engines (ISEs), namely, Google, Yahoo and Ask, are selected. Then, fifteen queries are determined from various topics and classified as one-, two- and three-word query groups.(More)
This paper investigates the information retrieval effectiveness of major image search engines based on various query topics. Initially, major image search engines, namely, Google, Yahoo, Ask and MSN are selected. Then, seven appropriate topics are determined from the categories of the top search terms used on the web and five queries per topic are chosen.(More)
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