The existing search engines sometimes give unsatisfactory search result for lack of any categorization of search result. If there is some means to know the preference of user about the search result and rank pages according to that preference, the result will be more useful and accurate to the user. In the present paper a web page ranking algorithm is being proposed based on syntactic classific...

Relying purely on query-page similarity when ranking Web search results limits the scope of the result set to the detriment of search performance. In this paper we propose that introducing diversity into the ranking metric can increase topic coverage without adversely affecting result relevance in the face of vague queries.

The Web grows at a fast pace and little is known about how new content is generated. The objective of this paper is to study the dynamics of content evolution in the Web, giving answers to questions like: How much new content has evolved from the Web old content? How much of the Web content is biased by ranking algorithms of search engines? We used four snapshots of the Chilean Web containing d...

Social Network Analysis is mapping and measuring of relationships and flows of information between people, organizations, computers, or other information or knowledge processing entities. Social media systems such as blogs, LinkedIn, you tube are allows users to share content media, etc. Blog is a social network notepad service with consider on user interactions. In this paper study the link pr...

Most ranking algorithms, such as pairwise ranking, are based on the optimization of standard loss functions, but the quality measure to test web page rankers is often different. We present an algorithm which aims at optimizing directly one of the popular measures, the Normalized Discounted Cumulative Gain. It is based on the framework of structured output learning, where in our case the input c...

Reasoning about agent preferences on a set of alternatives, and the aggregation of such preferences into some social ranking is a fundamental issue in reasoning about uncertainty and multiagent systems. When the set of agents and the set of alternatives coincide, we get the ranking systems setting. A famous type of ranking systems are page ranking systems in the context of search engines. In th...

Reasoning about agent preferences on a set of alternatives, and the aggregation of such preferences into some social ranking is a fundamental issue in reasoning about multi-agent systems. When the set of agents and the set of alternatives coincide, we get the ranking systems setting. A famous type of ranking systems are page ranking systems in the context of search engines. Such ranking systems...

We participated in the iUnit ranking subtask and the iUnit summarization subtask of the NTCIR-12 MobileClick for the Japanese and English languages. Our strategy is based on link analysis on an iUnit-page bipartite graph. First, we constructed an iUnit-page bipartite graph considering the entailment relationship between the iUnits and the pages. Then, we ranked the iUnits by their scores based ...

We investigate the application of a novel relevance ranking technique, cover density ranking, to the requirements of Web-based information retrieval, where a typical query consists of a few search terms and a typical result consists of a page indicating several potentially relevant documents. Traditional ranking methods for information retrieval, based on term and inverse document frequencies, ...

We developed the Biomedical Informatics Researchers ranking website (rank.informatics-review.com) to overcome many of the limitations of previous scientific productivity ranking strategies. The website is composed of four key components that work together to create an automatically updating ranking website: (1) list of biomedical informatics researchers, (2) Google Scholar scraper, (3) display ...