Physical Sciences and Mathematics Commons^™

Opems: Online Peer-To-Peer Expertise Matching System, Sharifullah Khan, S.M. Nabeel

International Conference on Information and Communication Technologies

Internet is a vital source to disseminate and share information to the masses. This has made information available in abundance on the Web. However, finding relevant information is difficult if not impossible. This difficulty is bilateral between information providers and seekers in terms of information presentation and accessibility respectively. This paper proposed an online Peer-to-Peer Expertise Matching system. The approach provides a highly scalable and self-organizing system and helps individuals in presenting and accessing the information in a consistent format on the Web. This makes the sharing of information among the autonomous organizations successful.

Visualization Of Retrieved Positive Data Using Blending Function, Muhammad Shoaib, Habib -Ur- Rehman, Dr. Abad Ali Shah

International Conference on Information and Communication Technologies

Data visualization is an important technique used in data mining. We present the retrieved data into visual format to discover features and trends inherent to the data. Some features of the data to be retrieved are already known to us. Visualization should preserve these known features inherent to the data. Positivity is one such known feature that is inherent to most of the scientific and business data sets. For example, mass, volume and percentage concentration are meaningful only when they are positive values. However certain visualization techniques do not guarantee to preserve this feature while constructing visualization of retrieved data …

Improving Document Representation By Accumulating Relevance Feedback : The Relevance Feedback Accumulation (Rfa) Algorithm, Razvan Stefan Bot

Dissertations

Document representation (indexing) techniques are dominated by variants of the term-frequency analysis approach, based on the assumption that the more occurrences a term has throughout a document the more important the term is in that document. Inherent drawbacks associated with this approach include: poor index quality, high document representation size and the word mismatch problem. To tackle these drawbacks, a document representation improvement method called the Relevance Feedback Accumulation (RFA) algorithm is presented. The algorithm provides a mechanism to continuously accumulate relevance assessments over time and across users. It also provides a document representation modification function, or document representation learning …

Integrating User Feedback Log Into Relevance Feedback By Coupled Svm For Content-Based Image Retrieval, Steven C. H. Hoi, Michael R. Lyu, Rong Jin

Research Collection School Of Computing and Information Systems

Relevance feedback has been shown as an important tool to boost the retrieval performance in content-based image retrieval. In the past decade, various algorithms have been proposed to formulate relevance feedback in contentbased image retrieval. Traditional relevance feedback techniques mainly carry out the learning tasks by focusing lowlevel visual features of image content with little consideration on log information of user feedback. However, from a long-term learning perspective, the user feedback log is one of the most important resources to bridge the semantic gap problem in image retrieval. In this paper we propose a novel technique to integrate the log …

Lightweight Federation Of Non-Cooperating Digital Libraries, Rong Shi

Computer Science Theses & Dissertations

This dissertation studies the challenges and issues faced in federating heterogeneous digital libraries (DLs). The objective of this research is to demonstrate the feasibility of interoperability among non-cooperating DLs by presenting a lightweight, data driven approach, or Data Centered Interoperability (DCI). We build a Lightweight Federated Digital Library (LFDL) system to provide federated search service for existing digital libraries with no prior coordination.

We describe the motivation, architecture, design and implementation of the LFDL. We develop, deploy, and evaluate key services of the federation. The major difference to existing DL interoperability approaches is one where we do not insist on …

Compressed Pattern Matching For Text And Images, Tao Tao

Electronic Theses and Dissertations

The amount of information that we are dealing with today is being generated at an ever-increasing rate. On one hand, data compression is needed to efficiently store, organize the data and transport the data over the limited-bandwidth network. On the other hand, efficient information retrieval is needed to speedily find the relevant information from this huge mass of data using available resources. The compressed pattern matching problem can be stated as: given the compressed format of a text or an image and a pattern string or a pattern image, report the occurrence(s) of the pattern in the text or image …

When Will Information Retrieval Be “Good Enough”?, James Allan

Computer Science Department Faculty Publication Series

We describe a user study that examined the relationship between the quality of an Information Retrieval system and the effectiveness of its users in performing a task. The task involves finding answer facets of questions pertaining to a collection of newswire documents over a six month period. We artificially created sets of ranked lists at increasing levels of quality by blending the output of a state-of-the-art retrieval system with truth data created by annotators. Subjects performed the task by using these ranked lists to guide their labeling of answer passages in the retrieved articles. We found that as system accuracy …

Incremental Test Collections, Ben Carterette, James Allan

Computer Science Department Faculty Publication Series

Corpora and topics are readily available for information retrieval research. Relevance judgments, which are necessary for system evaluation, are expensive; the cost of obtaining them prohibits in-house evaluation of retrieval systems on new corpora or new topics. We present an algorithm for cheaply constructing sets of relevance judgments. Our method intelligently selects documents to be judged and decides when to stop in such a way that with very little work there can be a high degree of confidence in the result of the evaluation. We demonstrate the algorithm's effectiveness by showing that it produces small sets of relevance judgments that …