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Given a set of keywords, we find a maximum Web query (containing the most keywords possible) that respects user-defined bounds on the number of returned hits. We assume a real-world setting where the user is not given direct access to a Web search engine's index, i.e., querying is possible only through an interface
Search engine marketing provided by search engines enable companies to promote their products to internet users based on their queries is now a major online advertising channel. In most search-based advertising services, advertisers could have dozens of keywords for the same product or service, and in most instances
Information search is one of the most common activities over Internet. Several search engines crawl the web round the clock and fetch useful information according to users' interest. To date, most of these search engines exploit the keyword based searching procedure which might be inappropriate for some naive users
In recent years, especially audiovisual media have become the predominant media of the internet. To enable content based video retrieval, high quality textual metadata have to be provided that describe the content. Keyword-based search in general is particularly applicable if the searcher really knows what she is
semantic net which can be applied to build personalized search engine and tested with single query keyword and multi ones by three different calculating policies. The test results show that it can affect the sort of pages. The personalized search based on vocabulary semantic net improves the quality of search results greatly.
In this paper, we propose the ldquoaddedrdquo use of proximity search to a Web search query for narrowing down the set of documents returned as answers to a keyword based search query. This approach adds value to Web search query results by allowing users to better express what they are looking for. Most of the
, for example) don't even enable keyword searches on their sites. The Web's increasingly dynamic nature complicates searching. New pages created on the fly using personalization information, and even static content, with dynamically inserted sidebars, navigation bars, advertising and commentary, can present a rapidly
Most researches on Image Retrieval (IR) have aimed at clearing away noisy images and allowing users to search only acceptable images for a target object specified by its object-name. We have become able to get enough acceptable images of a target object just by submitting its object-name to a conventional keyword
the registered bidders. Given (1) the valuation of the advertisers competing for sponsored slots corresponding to a keyword, and (2) relevant click-through rates, the proposed algorithm generates a bid profile that can be input to a standard generalized second price based sponsored search auction mechanism. The bid
When we use a search engine in Internet, we often cannot retrieve a document we look for, due to the difficulty of finding adequate keywords. One of the ways to solve the problem is to search adequate keywords interacting with a user: a metasearch engine displays keywords and pages, a user evaluate them. Iterating the
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
As an approach to search /retrieve such objects as pictures, music, perfumes and apparels on the Internet, sensitivity-vectors or kansei-vectors are useful since textual keywords are not sufficient to find objects that users want. The sensitivity-vector is an array of values each indicates a degree of feeling or
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