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HOW TO OPTIMIZE THE QUERYING OF TEXTUAL QUERIES WHEN SEARCHING ON THEWEB FOR AMULTILINGUAL INFORMATION SEARCH?
Abstract
The web has become a very important source of information for users (students, researchers, general public, etc.) and commercial enterprises. This propulsion of data is related to the diversity of requests for information and the need for versatile knowledge. Access to digital data via web services is facilitated by search tools. Following a request from the user, the search engine has a long list of informational responses, but often containing parasitic pages. Although before the appearance of the web, the search for information was considered as an activity intended for professionals of the library, today any user with a need for information can carry out a search and have instant access to a monumental mass of results. However, the problem that has emerged from the popularization of information retrieval (IR) is that the results obtained through natural language queries are often noisy or contain a lot of silence. In addition, the formulation of requests is another problem that can hinder the search for information on the web. In fact, the information requester launches a single query with a few terms and is often in a hurry and rarely takes the time to reread his request before launching it. Similarly, by querying search engines containing Boolean operators, proximity characters, or specific characters, intra-query errors have become one of the limitations of finding information on the Web in either simple mode or expert. Faced with this gap, search engines have tried to improve their performance in order to provide the most relevant results to the user. However, in the context of multilingual information retrieval, search engine algorithms struggle to achieve perfect completeness that would prevent intra-query errors from impacting the relevance of the results provided. Thus, the problem of this article is to observe how search engine performance can provide relevant results, and what the strategies for finding hidden information without. As such, the goal is to see if, during a web query, it is possible to retrieve information in other languages, in addition to the source language. Current indexes consist of multilingual composite content. Our goal is to assess the granularity of words when searching for multilingual information with a focus on the assessment of SERP of Google.fr, Google.ru, Google.dz, Google.hk, Yahoo.fr, and Bing.fr.
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