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In this work we aim to capitalize on the availability of Internet image search engines to automatically create image training sets from user provided queries. This problem is particularly difficult due to the low precision of image search results. Unlike many existing dataset gathering approaches, we do not assume a category model based on a small subset of the noisy data or an ad-hoc validation set...
party servers. In this paper, we discuss on the authenticated search results of some recent works and then present an improved scheme that ensures the authenticity of the search results corresponding to a search query over Internet. The improved scheme is based on the scheme [1] that uses the concept of conjunctive keyword
effective in terms of better precision. Proposed method makes use of keyword clusters for query expansion. Visual features are used for detecting duplicate images in proposed method. Removing duplicates leads to further improve in precision and recall in retrieval result
propose a """"Hybrid Search Engine Framework for the Internet of Things based on Spatial-Temporal, Value-based, and Keyword-based Conditions"""" (""""IoT-SVK Search Engine"""" for short). The experimental results
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
An individual's problem space has been identified as important in problem solving. A problem space is a person's inner representation of the task after extracting critical components in the external problem task. This paper proposes a study to probe whether there are different problem spaces for efficient and inefficient Web information searchers. The questions will be answered quantitatively using...
An ever-increasing amount of information on the Web today is available only through search interfaces: the users have to type in a set of keywords in a search form in order to access the pages from certain Web sites. These pages are often referred to as the hidden Web or the deep Web. Since there are no static links
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
Language Model (LM) constitutes one of the key components in Keyword Spotting (KWS). The rapid development of the World Wide Web (WWW) makes it an extremely large and valuable data source for LM training, but it is not optimal to use the raw transcripts from WWW due to the mismatch of content between the web corpus
Search engines award their advertising space through keyword auctions. Some bidders may adopt an aggressive bidding strategy known as Competitor Busting, where they submit higher bids than what is strictly needed to win the auction so as to oust the other bidders. Despite the widespread concern for such practice, we
issued to the databases also contain spatial and textual components, for example, "Find shelters with emergency medical facilities in Orange County," or "Find earthquake-prone zones in Southern California." We refer to such queries as spatial-keyword queries or SK queries for short. In recent times, a lot of interest has
The total information available on WWW (World Wide Web) is huge and is increasing at lightning speed. Existing web is dominated by Search Engines which are running on keyword based search system which in turn leads to wastage of end user's precious time if he do not know the key terms which are utilized to index
Keyword search (KWS) over relational data, where the answers are multiple tuples connected via joins, has received significant attention in the past decade. Numerous solutions have been proposed and many prototypes have been developed. Building on this rapid progress and on growing user needs, recently several RDBMS
Processing short texts is becoming a trend in information retrieval. Since the text has rarely external information, it is more challenging than document. In this paper, keyword clustering is studied for automatic categorization. To obtain semantic similarity of the keywords, a broad-coverage lexical resource WordNet
Keyword generation for search engine advertising is an important problem for sponsored search or paid-placement advertising. A recent strategy in this area is bidding on nonobvious yet relevant words, which are economically more viable. Targeting many such nonobvious words lowers the advertising cost, while delivering
A dynamic population model is proposed for the study of keyword auctions run on search engines. In this model bidders decide to join or leave the auction, depending on the results of the previous auction round. Through the use of a simulation scenario, we show that the model converges to a steady state quite fast, and
A keyword choice and analysis approach in SEO is studied to deal with the issues such as low efficiency, poor reliability and instability optimization in artificial SEO processing in this paper. A keyword expansion method is proposed by reversing search engine's related search keywords to meet user's requirements
In this paper, we propose a novel image search scheme is contextual image search with keyword input. It is different from conventional image search schemes. it consist of three step process, first one is context extraction to distinguish the image entities of the same name, second step is conceptualization to convert
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