Improving web scale discovery services

This article reviews the current state of web scale discovery (WSD) services and their effectiveness in providing a viable interface for initiating literature searches.  Some of the shortcomings are discussed, as well as developments that are under way or necessary in order to improve the concept of single searching. Aspects discussed include indexing, relevance ranking, publication finders, linking mechanisms, and personalization of searches. The relationship between publishers and WSD providers is all-important in improving the end-user experience

An Adaptive Cross-Site User Modelling Platform for Information Exchange Techniques

The objective of the thesis is to build an adaptive Cross Site User Modelling platform for information exchange techniques in order to identify and evaluate such information exchange mechanisms. The information exchange mechanisms provide useful information to target websites that can use it to personalise the user browsing experience

A Component-Based Approach for Scientific Services for Education and Research (Scientific SEARCH)

Today’s challenge for retrieving digital information by users such as “students,” educators,” or “researchers” is coping, more than ever before, with the excessive data and information available. The problem is further compounded because of the way scientific knowledge is structured, in terms of expert interviews, articles, conference coverage, journal scans etc. Great progress has been made in digital library research. The NSF/NSDL through their initiatives has assembled a great set of tools and techniques that hold significant potential. Many projects are now underway applying these tools and techniques to meet the information needs of different user communities. The primary focus of Scientific SEARCH project is enhancing access to high quality learning materials and resources, modules, and other digital objects targeted towards scientific consumer and scientific producer. The project will use a multi-phased approach to achieve the objective. The paper describes the first-phase work submitted to NSF 04-542 solicitation

The Potential of Bookmark Based User Profiles

Driven by the explosive growth of information available online, the World-Wide-Web is currently witnessing a trend towards personalized information access. As part of this trend, numerous personalized news services are emerging. The goal of this project is to develop a prototype algorithm for using bookmarks to develop a personal profile. Ultimately, we imagine this might be used to construct a personalized RSS reader for reading news online. A reader returns a large number of news stories. To increase user satisfaction it is useful to rank them to bring the most interesting to the fore. This ranking is done by implementing a personalized profile. One way to create such a profile might be to extract it from user's bookmarks. In this paper, we describe a process for learning user interest from bookmarks and present an evaluation of its effectiveness. The goal is to utilize a user profile based on bookmarks to personalize results by filtering and re-ranking the entries returned from a set of user defined feeds

An Efficient Information Extraction Mechanism with Page Ranking and a Classification Strategy based on Similarity Learning of Web Text Documents

Users have recently had more access to information thanks to the growth of the www information system. In these situations, search engines have developed into an essential tool for consumers to find information in a big space. The difficulty of handling this wealth of knowledge grows more difficult every day. Although search engines are crucial for information gathering, many of the results they offer are not required by the user because they are ranked according on user string matches. As a result, there were semantic disparities between the terms used in the user inquiry and the importance of catch phrases in the results. The problem of grouping relevant information into categories of related topics hasn't been solved. A Ranking Based Similarity Learning Approach and SVM based classification frame work of web text to estimate the semantic comparison between words to improve extraction of information is proposed in the work. The results of the experiment suggest improvisation in order to obtain better results by retrieving more relevant results

Search in the eye of the beholder: using the personal social dataset and ontology-guided input to improve web search efficiency

Proceedings of: Latin American Web Conference 2007 (LA-WEB 2007), 31 October-2 November 2007, Santiago (Chile)Among the challenges of searching the vast information source the Web has become, improving Web search efficiency by different strategies using semantics and the user generated data from Web 2.0 applications remains a promising and interesting approach. In this paper, we present the Personal Social Dataset and Ontology-guided Input strategies and couple them together, providing a proof of concept implementation.Publicad

Intelligent agents for matching information providers and consumers on the World-Wide-Web

In this paper, we discuss the various issues in designing intelligent software systems to assist world-wide-web users in locating relevant information. We identify a number of key components in such intelligent systems. These include a web document database management system, a client-based goal-directed search engine, an intelligent learning agent which discovers users' topics of interest by studying their browsing behavior, and an intelligent agent which monitors `hot' web sites. We give examples and suggestions on how these components are designed and implemented. We also describe the architecture of a prototype system that integrates the various components.published_or_final_versio