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Keyword auctions are being used to sell the positions along the side of organic results shown by search engine when user types a keyword or a query related to keyword in a search engine. It has been a huge revenue generating arena for search engines since last decade. Irrespective of the great success of these types
In general, content-based recommender systems use a keyword vector to locate recommendations. However, this method does not consider relations of each keyword and it is also inscrutable to users, who may have a hard time determining which words in their profiles are important and which may be skewing their results to
With the development of Internet, more and more on-line information has become precious wealth that we can access to. High quality information is often stored in dedicated digital libraries. However, query system of most digital libraries based on keyword matching couldnpsilat make users satisfied. This paper presents
the crawled Web pages in to repositories. At first, the keywords are extracted from the crawled pages and the similarity score between two pages is calculated based on the extracted keywords. The documents having similarity scores greater than a threshold value are considered as near duplicates. The detection has
improve the performance of English-Hindi CLIR system using English and Hindi WordNet, Local Expansion using initial query, definition based pre query expansion and keyword ranking. The pre and post query expansion helps to improving the performance of English-Hindi CLIR system and based upon past experiences the proposed
results in up to 1.1% absolute Word Error Rate (WER) improvement as compared to keyword-based approaches. The proposed approach reduces the WER by 6.3% absolute in our experiments, compared to an in-domain LM without considering any Web data.
query-keywords are used as a basis for sentence extraction. Results obtained from experiments performed have shown that such a combined approach can provide very interesting similarity calculation and re-ranking measure. This can be used with reasonable efficiency to detect duplications on search results generated by
In this research, we used a proxy server to search for information related to the userpsilas browsed Web pages. From the records of the proxy server we constructed a profile of the userpsilas browsing habits. At the end of the userpsilas search subsystem, we will use content based concept to extract keywords to obtain
Bid optimization is now becoming quite popular in sponsored search auctions on the Web. Given a keyword and the maximum willingness to pay of each advertiser interested in the keyword, the bid optimizer generates a profile of bids for the advertisers with the objective of maximizing customer retention without
In this paper, we examine the significance of expansion of the user query by two techniques namely Efficient Clustering-By-Direction and Theme Clustering. These two techniques produce the clusters of keywords extracted from the set of retrieved documents for the user query. The former clustering is based on
In this paper, we propose a new method to select relevant images to the given keywords from the images gathered from the Web. Our novel method is based on the probabilistic latent semantic analysis (PLSA) model, which is a generative probabilistic topic model. Firstly, we gather images related to the given keywords
Islamic forums on the Dark Web which are made available for security research. This research project uses a POS tagger to isolate keywords and nouns that can be utilized with the sentiment analysis program. Then the sentiment analysis program determines the polarity of the post. The post is scored as either positive or
ontologies.The web interface allows video browse, query by annotated concepts or by keywords, compressed video preview, media download and upload. The repository contains metadata annotations, which can be either manually created as ground truth or automatically generated by video surveillance systems. Their automatic annotations
To discovery Web services in Internet, many approaches have been proposed such as UDDI and DWS. The problem of those methods is that they are just a kind of simple syntax match based on keywords. They make the match inflexible, sometimes even unfaithful. This paper proposes a new algorithm to discover web services
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