Text extraction and Web searching in a non-Latin language

Recent studies of queries submitted to Internet Search Engines have shown that non-English queries and unclassifiable queries have nearly tripled during the last decade. Most search engines were originally engineered for English. They do not take full account of inflectional semantics nor, for example, diacritics or the use of capitals which is a common feature in languages other than English. The literature concludes that searching using non-English and non-Latin based queries results in lower success and requires additional user effort to achieve acceptable precision. The primary aim of this research study is to develop an evaluation methodology for identifying the shortcomings and measuring the effectiveness of search engines with non-English queries. It also proposes a number of solutions for the existing situation. A Greek query log is analyzed considering the morphological features of the Greek language. Also a text extraction experiment revealed some problems related to the encoding and the morphological and grammatical differences among semantically equivalent Greek terms. A first stopword list for Greek based on a domain independent collection has been produced and its application in Web searching has been studied. The effect of lemmatization of query terms and the factors influencing text based image retrieval in Greek are also studied. Finally, an instructional strategy is presented for teaching non-English students how to effectively utilize search engines. The evaluation of the capabilities of the search engines showed that international and nationwide search engines ignore most of the linguistic idiosyncrasies of Greek and other complex European languages. There is a lack of freely available non-English resources to work with (test corpus, linguistic resources, etc). The research showed that the application of standard IR techniques, such as stopword removal, stemming, lemmatization and query expansion, in Greek Web searching increases precision.