Yielding precise search answer set, information extraction of the Web and proposing more accurate ranking methods of Web pages are among the open issues in search engines research area due to the ever-growing and dynamic nature of the World Wide Web. Since the performance of any Web search engine regarding the quality of the search answer set and the appropriate ranking technique is highly depe...

Contemporary Internet search engine can hardly cope with enormous amount of indexed data, and very seldom succeed in extracting useful information. In order to anticipate usefulness of a web page, proposed solution keeps track of users actions on a web page. A modified web client informs a dedicated server of users' actions performed on a web page, such as printing, bookmarking or mailing. Latt...

This is the first year that members of the Database and Information System Lab (DBIS) at University of Illinois at Chicago (UIC) participate in TREC. We participate in two tasks for the Web track: topic distillation and named page finding. Linkage information among documents as well as content information about documents is used in some of our submitted runs. We utilize the Okapi weighting sche...

Technologies supporting online education have been abundantly developed recent years. Many repositories of digital learning resources have been set up and many recommendation approaches have been proposed to facilitate the consummation of learning resources. In this paper, we present an approach that combines three recommendation technologies: content-based filtering, word semantic similarity a...

Existing search engines contain the picture of the Web from the past and their ranking algorithms are based on data crawled some time ago. However, a user requires not only relevant but also fresh information. We have developed a method for adjusting the ranking of search engine results from the point of view of page freshness and relevance. It uses an algorithm that postprocesses search engine...

Received Jan 7, 2018 Revised Feb 16, 2018 Accepted Feb 22, 2018 Ranking algorithms based on link structure of the network are well-known methods in web search engines to improve the quality of the searches. The most famous ones are PageRank and HITS. PageRank uses probability of random surfers to visit a page as the score of that page, and HITS instead of produces one score, proposes using two ...

This is the first year that members of the Database and Information System Lab (DBIS) at University of Illinois at Chicago (UIC) participate in TREC. We participate in two tasks for the Web track: topic distillation and named page finding. Linkage information among documents as well as content information about documents is used in some of our submitted runs. We utilize the Okapi weighting sche...

The WWW today is overwhelmed with information on almost every topic. Therefore, relevance ranking of web pages to a user’s expectations is a challenge, rather than retrieving a collection of thousands of web pages selected by keyword matching. This paper presents an approach to rank tagged web pages retrieved from a Social Bookmarking Site for a learner who needs web resources containing conten...

Web content mining retrieves the information from web in more structured forms. The page rank plays an essential part process. Whenever user searches for any on web, relevant is shown at top of list through ranking. Many existing ranking algorithms were developed and failed to pages accurate manner minimum time feeding. In direction address above mentioned issues, Lancaster Stem Sammon Projecti...