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Search engines have turn out to be the most effective tools for acquiring useful information from the Internet. Different techniques are employed for searching desired documents from the World Wide Web. Most of them are either change the entered query or apply different ranking methods to adapt the searching results for particular person. This paper introduces a system (PSQCR) that produces personalized...
Online shopping has developed to a stage where catalogs have become very large and diverse. Thus, it is a challenge to present relevant items to potential customers within a very few interactions. This is even more so when users have no defined shopping objectives but operate in an opportunistic mindset. This problem is often tackled by recommender systems. However, these systems rely on consistent...
Modern society is characterized by abundance of data, yet lack of (relevant) information. A major challenge consists in selecting valuable information according to specific criteria. Moreover, ranking it and defining relevance according to the context is decisive. We propose a framework to retrieve content according to context. Our approach relies on a three layers model, each contributing to a better...
Keyword based search scheme imposes the problem of representing a lot of web pages in the search engines. Query expansion with relevant words increases the performance of search engines, but finding and using the relevant words is an open problem. In this research we describe a new model for query expansion which employs user context and semantic concepts to discover new words for obtaining accurate...
Web services technology is widely used as a solution of information by all users. Now a days, the user rely on web for the information need but the currently available search engines though using sophisticated document indexing algorithms, quite often gives a long list of results, much of which are not always relevant to the user's requirement. Since a user has a specific goal when searching for information,...
Data prefetching is an effective way to accelerate data access in high-end computing systems and to bridge the increasing performance gap between processor and memory. In recent years, the context based data prefetching has received intensive attention because of its general applicability. In this study, we provide a preliminary analysis of the impact of orders on the effectiveness of the context-based...
We present a novel approach intended to reduce user effort required to retrieve and/or revisit previously discovered information by exploiting web search and navigation history. In our approach, we collect streams of user actions during search and navigation sessions, identify individual user goals and construct and persistently store visual trees representing session history. We provide users with...
Online support centers are emerging as a cost-effective and innovative solution designed to enable end-users to resolve technical problems more effectively without relying on live support from contact center agents. However, the capacity limitation of corporate knowledge bases prevents online support centers from effectively resolving user problems. In addition, traditional textual search techniques...
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