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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
Semantic and keyword web based technique is becoming a generic issue in an application of Information Retrieval (IR). Most of the researchers used different web techniques for finding relevant information and find the keyword based search, which are not able to fetch the relevant search result because they do not know
confusion of information, disguise, and invalidation of correlation weighing when current text mining techniques based on keyword search are employed to conduct technology forecasting. In this paper, we present a three-layer model of smart technology forecasting based on text mining consisting of the collection layer, the
Traditional web service search technology based on keyword is time consuming and inefficient. The search results are rather inaccurate. The essential reason is that description of Web Service lacks semantic information. Search Engines can't achieve the interaction automatically and intelligently among services. In
shortlist the results. These popular Web search engines use first generation search service based on ??static keywords??, which require the users to type in the exact keywords. This approach clearly puts the users in a critical situation of guessing the exact keyword. The users may want to define their search by using
creative ideas to customers. In order to solve this problem, this paper presents algorithms to achieve customers' target. This project can be divided into three parts. The first part is to enrich and to analyse the input keywords by semantic web. The second part is to general raw ideas and relevant ideas by an inference
Information retrieval becomes a very complex process for search engines on the Web, this is due to, first, the staggering growth speed of the number of web site and, in the other hand, the search algorithms by keywords (terms) used currently are not suitable to better exploit this huge information quantity. These
On account of the weakness of the current search engine, we put forward the concept of semantic search. Integrated with the unstructured information management architecture (UIMA) of IBM, we can make search not only just base on the search of keywords, but through the comprehension of the unstructured information to
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