The World Wide Web (WWW) is a fast growing network of information covering nearly every possible topic. With the input of a few keywords a search engine can return a list of relevant web pages by querying its index. However, it is quite common to witness irrelevant results being presented to the user. One way to improve the ordering of the search results is by incorporating user feedback in ran...

with the explosive growth of the transmission knowledge on the Web, content-based image search has attracted considerable attentions within the transmission and computer vision community. The most common approach is predicated on the bag-of-visual-words model with invariant native options. Since the special context information among native options is important for visual content identification,...

In the standard model of sponsored search auctions, an ad is ranked according to the product of its bid and its estimated click-through rate (known as the quality score), where the estimates are taken as exact. This paper re-examines the form of the efficient ranking rule when uncertainty in click-through rates is taken into account. We provide a sufficient condition under which applying an exp...

The rapid production of digital information has made the task of locating relevant information increasingly difficult. Keyword search alleviates this difficulty by retrieving documents containing keywords of interest, but suffers from issues such as ambiguity and synonymity. Semantic search resolves these issues, but is limited by the quality of semantic annotations that are likely to be imprec...

In this paper, an improved technique for contingency ranking using artificial neural network (ANN) is presented. The proposed approach is based on multi-layer perceptrons trained by backpropagation to contingency analysis. Severity indices in dynamic stability assessment are presented. These indices are based on the concept of coherency and three dot products of the system variables. It is well...

Recommender systems are becoming increasingly important to individual users and businesses for providing personalized recommendations. However, while the majority of algorithms proposed in recommender systems literature have focused on improving recommendation accuracy (as exemplified by the recent Netflix Prize competition), other important aspects of recommendation quality, such as the divers...

This paper gives brief idea about new approach towards E learning in Micro-blogging supported classroom. Micro-blogging is a technology used in social networking applications which can be used in classroom for the communication between student and teacher. Nowadays from research it is observed that it has numerous benefits. Its major advantage is that the number of questions asked is much more ...

Statistical selection procedures are used to select the best simulated system from a finite set of alternatives. In this paper, we present a procedure that can be used to select the best system when the number of alternatives is large. The proposed procedure consists a combination between Ranking and Selection, and Ordinal Optimization procedures. In order to improve the performance of Ordinal ...

In keyword search over data graphs, an answer is a nonredundant subtree that contains the keywords of the query. Ranking of answers should take into account both their textual relevance and the significance of their semantic structure. A novel method for answers priors is developed and used in conjunction with query-dependent features. Since the space of all possible answers is huge, efficiency...

The main objective is to develop a technique for classifying the lung tissue as well as finding lung cancer and ranking its severity. To classify the lung tissue the existing system is used. In the existing system Sparse based features are used for classification. In proposed system the lung cancer is detected and segmented. To do this the bee colony technique is used. Before applying the bee c...