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The World Wide Web has immense resources for all kind of people for their specific needs. Searching on the Web using search engines such as Google, Bing, Ask have become an extremely common way of locating information. Searches are factorized by using either term or keyword sequentially or through short sentences. The
Keyword auctions were widely used by search engines to sell the advertisement on the result pages. To date, the most widely used auction mechanism is wGSP (weighted and generalized second-price). This paper presents an optimal pricing strategy under wGSP for advertiser to bid keywords for their websites. In brief, the
We propose a Discovery approach to find web services composition flows sorted by similarity. The approach extracts information from BPEL files. When creating new web services composition, the discovery result can be reused directly or provide reference. We import the lexical semantic in matching keywords. By analysis
This paper described our development dialog system on Kyoto tourist information assistance. Dialog part of our system helped user to make an appropriate query. Information analysis part would be assisted for user to select the retrieved information. Nowadays we can get most information through the Internet. However, we have a trouble to pick up expected information from the huge results with conventional...
The World Wide Web is growing at a rate of about a million pages per day, making it tougher for search engines to extract relevant information for its users. Earlier Search Engines used simple indexing techniques to search for keywords in websites and gave more weightage to pages with higher frequency of keyword
this job fairly well, but does not perform as well when the feedback information is only about non-relevant webpages. In such an unfavorable circumstance the legwork mechanism assists the suggesting module by handing over the relevant information after finding one or more webpages, containing at least one clue keyword
Previous multikeyword search in DHT-based P2P systems often relies on multiple single keyword search operations, suffering from unacceptable traffic cost and poor accuracy. Precomputing term-set-based index can significantly reduce the cost but needs exponentially growing index size. Based on our observations that 1
The existing search engine system almost based on keywords from users inputting. In a network environment, people can make use of the pc or mobile device for information retrieval. The way of inputting keywords has lasted for more than 20 years until Siri appeared in 2011. Siri can do information retrieval and process
In order to solve the limitations of most of the current search engines only through the user's handwriting input keywords to read information, described new search engine system based on computer vision. Containing the information search and problem solve two basic parts. And for the needs of the people in daily
In order to study the retrieval precision of network information and solve the problems existed in search engines this paper analyzes problems and precision in the information retrieval according to experimental data such as image retrieval with different retrieval keywords, and puts forward a new construction of
It has become common to search necessary services and contents using the Internet, but it is difficult to find exactly what one is looking for through keywords as each service is described in just too many ways. We developed "laddering" search service system that matches the needs of the users with the search targets
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
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.