42232021
On User-oriented Measurements of Effectiveness of Web Information Retrieval Systems
28060413
The Architecture of Yarrow: A Real-Time Intelligent Meta-Search Engine
44651708
Personalized Web Search with Clusters
7399730
An Almost Linear Time 2.8334-Approximation Algorithm for the Disc Covering Problem
The disc covering problem asks to cover a set of points on the plane with a minimum number of fix-sized discs. We develop an O(n(logn)2(loglogn)2) deterministic time 2.8334-approximation algorithm for this problem. Previous approximation algorithms [7,3,6], when used to achieve the same approximation ratio for the disc covering problem, will have much higher time complexity than our algorithms.
140623
Optimal Algorithms for Finding User Access Sessions from Very Large Web Logs
Although efficient identification of user access sessions from very large web logs is an unavoidable data preparation task for the success of higher level web log mining, little attention has been paid to algorithmic study of this problem. In this paper we consider two types of user access sessions, interval sessions and gap sessions. We design two efficient algorithms for finding respectively those two types of sessions with the help of some proposed structures. We present theoretical analysis of the algorithms and prove that both algorithms have optimal time complexity and certain error-tolerant properties as well. We conduct empirical performance analysis of the algorithms with web logs ranging from 100 megabytes to 500 megabytes. The empirical analysis shows that the algorithms just take several seconds more than the baseline time, i.e., the time needed for reading the web log once sequentially from disk to RAM, testing whether each user access record is valid or not, and writing each valid user access record back to disk. The empirical analysis also shows that our algorithms are substantially faster than the sorting based session finding algorithms. Finally, optimal algorithms for finding user access sessions from distributed web logs are also presented.
5722664
A Visualization System using Data Mining Techniques for Identifying Information Sources
The Visual Analysis System (VAS) was developed to couple emerging successes in data mining with information visualization techniques in order to create a richly interactive environment for information retrieval from the World Wide Web. VAS's retrieval strategy operates by first using a conventional search engine to form a core set,of retrieved documents. This core set is expanded by crawling from links in these documents to form a much larger set. The link topology of the larger set is then examined using data mining techniques to identify pages likely to be both relevant to the query and reliable as sources of information. Information visualization techniques are used to display the filtered set in a form amenable to the use of perceptual processes to filter and guide further user directed search. (Contains 16 references.) (MES) Reproductions supplied by EDRS are the best that can be made from the original document. N tr) 00 7171A Visualization System using Data Mining Techniques for Identifying Information Sources Richard H. Fowler, Tarkan Karadayi, Zhixiang Chen, Xiannong Meng, Wendy A. Lawrence Fowler Department of Computer Science University of Texas Pan American United States {fowler, tkaradayi, chen, meng, wfowler @panam.edu} PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY
2042582
Pose determination of a cylinder using reprojection transformation
Extracting useful and robust feature points from a cylinder image for 3D pose determination is a relatively difficult task, since there are no feature points or lines on the cylinder. In this study, a key vector from a cylinder image is found to yield a transformation. The cylinder is then ''reprojected'' from the original image to obtain a new image using the transformation. The new image reveals some important features capable of determining the 3D cylinder position robustly. The proposed method can yield an exact and analytical solution without the requirement of using any special marks, extra equipment or assumptions. Additionally, a problem in which both circles on the cylinder are not completely visible due to the viewing angle can be resolved by this method. Finally, experimental results are provided to verify the theory and show the robustness of our method.
25781895
Web page clustering enhanced by summarization
Traditional Web page clustering algorithms use the full-text in the documents to generate feature vectors. Such methods often produce unsatisfactory results because there is much noisy information, such as decoration, interaction, and advertisement, in Web pages. The varying-length problem of the Web pages is also a significant negative factor affecting the performance. In this paper, we investigate the use of several summarization techniques to tackle these issues when clustering Web pages. Compared with the full-text representation of the Web pages, our experimental results indicate that our proposed approach effectively solves the problems of noisy information and varying-length, and thus significantly boosts the clustering performance.
1830855
Web mining for Web image retrieval
The popularity of digital images is rapidly increasing due to improving digital imaging technologies and convenient availability facilitated by the Internet. However, how to find user-intended images from the Internet is non-trivial. The main reason is that the web images are usually not annotated using semantic descriptors. In this paper, we present an effective approach to and a prototype system for image retrieval from the Internet using web mining. The system can also serve as a web image search engine. One of the key ideas in the approach is to extract the text information on the web pages to semantically describe the images. The text description is then combined with other low-level image features in the image similarity assessment. Another main contribution of this work is that we apply data mining on the log of user’s feedback to improve image retrieval performance in three aspects: First, the accuracy of the document space model of image representation obtained from the web pages is improved by removing clutter and irrelevant text information; Second, to construct the user space model of users’ representation of images, which is then combined with the document space model to eliminate mismatch between the page author’s expression and the user’s understanding and expectation; Third, to discover the relationship between low-level and high-level features, which is extremely useful for assigning the low-level features’ weights in similarity assessment.
5809396
Self-adapting numerical software (SANS) effort
The challenge for the development of next-generation software is the successful management of the complex computational environment while delivering to the scientist the full power of flexible compositions of the available algorithmic alternatives. Self-adapting numerical software (SANS) systems are intended to meet this significant challenge. The process of arriving at an efficient numerical solution of problems in computational science involves numerous decisions by a numerical expert. Attempts to automate such decisions distinguish three levels: algorithmic decision, management of the parallel environment, and processor-specific tuning of kernels. Additionally, at any of these levels we can decide to rearrange the user's data. In this paper we look at a number of efforts at the University of Tennessee to investigate these areas.
15310025
A study of relevance propagation for web search
Different from traditional information retrieval, both content and structure are critical to the success of Web information retrieval. In recent years, many relevance propagation techniques have been proposed to propagate content information between web pages through web structure to improve the performance of web search. In this paper, we first propose a generic relevance propagation framework, and then provide a comparison study on the effectiveness and efficiency of various representative propagation models that can be derived from this generic framework. We come to many conclusions that are useful for selecting a propagation model in real-world search applications, including 1) sitemap-based propagation models outperform hyperlink-based models in sense of both effectiveness and efficiency, and 2) sitemap-based term propagation is easier to be integrated into real-world search engines because of its parallel offline implementation and acceptable complexity. Some other more detailed study results are also reported in the paper.