Search

A large part of the hidden web resides in weblog servers. New content is produced in a daily basis and the work of traditional search engines turns to be insufficient due to the nature of weblogs. This work summarizes the structure of the blogosphere and highlights the special features of weblogs. In this paper we present a method for ranking weblogs based on the link graph and on several similarity characteristics between weblogs. First we create an enhanced graph of connected weblogs and add new types of edges and weights utilising many weblog features. Then, we assign a ranking to each weblog using our algorithm, BlogRank, which is a modified version of PageRank. For the validation of our method we run experiments on a weblog dataset, which we process and adapt to our search engine. (http://spiderwave.aueb.gr/Blogwave). The results suggest that the use of the enhanced graph and the BlogRank algorithm is preferred by the users., Comment: 9 pages, in 2nd international workshop on Advanced architectures and algorithms for internet delivery and applications

When searching the web, it is often possible that there are too many results available for ambiguous queries. Text snippets, extracted from the retrieved pages, are an indicator of the pages' usefulness to the query intention and can be used to focus the scope of search results. In this paper, we propose a novel method for automatically extracting web page snippets that are highly relevant to the query intention and expressive of the pages' entire content. We show that the usage of semantics, as a basis for focused retrieval, produces high quality text snippet suggestions. The snippets delivered by our method are significantly better in terms of retrieval performance compared to those derived using the pages' statistical content. Furthermore, our study suggests that semantically-driven snippet generation can also be used to augment traditional passage retrieval algorithms based on word overlap or statistical weights, since they typically differ in coverage and produce different results. User clicks on the query relevant snippets can be used to refine the query results and promote the most comprehensive among the relevant documents., Comment: In proceedings of SIGIR 2007 Workshop on Focused Retrieval. 8 pages