44651708
Personalized Web Search with Clusters
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
28060413
The Architecture of Yarrow: A Real-Time Intelligent Meta-Search Engine
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.
14422953
On-line learning of rectangles
This paper solves the following open problem: Is there an algorithmfor on-line learning of rectangles <inline-equation><f><pr align="c"><ll>i=1</ll><ul>d</ul></pr></f><?Pub Caret></inline-equation><?Pub Fmt italic>a<subscrpt>i</subscrpt>,a<subscrpt>i</subscrpt>+1,…,b<subscrpt>i</subscrpt>}<?Pub Fmt /italic>over a discrete domain<?Pub Fmt italic>{1,…,n}<supscrpt>d</supscrpt><?Pub Fmt /italic>whose error bound is polylogarithmic in the size<?Pub Fmt italic>n<supscrpt>d</supscrpt><?Pub Fmt /italic> of the domain(i.e. polynomial in <?Pub Fmt italic>d<?Pub Fmt /italic> and log<?Pub Fmt italic>n<?Pub Fmt /italic> )? We give a positive solution byintroducing a new design technique that appears to be of some intereston its own. The new learning algorithm for rectangles consists of<?Pub Fmt italic>2d<?Pub Fmt /italic> separate search strategies thatsearch for the parameters <?Pub Fmt italic>a<subscrpt>1</subscrpt>,b<subscrpt>1</subscrpt>,…,a<subscrpt>d</subscrpt>,b<subscrpt>d</subscrpt><?Pub Fmt /italic>of the target rectangle. A learning algorithm with this type of modulardesign ends to fail because of the well known “credit assignmentproblem”: Which of the <?Pub Fmt italic>2d<?Pub Fmt /italic> localsearch strategies should be “blamed” when the globalalgorithm makes an error? We overcome this difficulty by employing localsearch strategies (“error tolerant binary search”) that areable to tolerate certain types of wrong credit assignments.
Section 4 contains another application of this design technique: analgorithm for learning the union of two rectangles in the plane.
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.
15432149
Ubiquitous media agents for managing personal multimedia files
A novel idea of ubiquitous media agents is presented. Media agents are intelligent systems that are able to automatically collect and build personalized semantic indices of multimedia data on behalf of the user whenever and wherever he/she accesses/uses these multimedia data. The sources of these semantic descriptions are the textual context of the same documents that contain these multimedia data. The URLs of these multimedia data are indexed using these textual features. When the user wants to use these multimedia data once again, the media agents can also help the user find relevant multimedia data and provide proper suggestions based on the semantic indices. The media agents can also learn form the user's interaction records to refine the semantic indices and to model the user intentions and preferences. In our experiments, the media agents are effective in gathering relevant semantics for media objects and learning to provide precise suggestions when the user wants to re-use relevant media objects again.
45057829
Preclassification of handwritten Chinese characters based on basic stroke substructures
A method for preclassification of handwritten Chinese characters is presented. A set of basic stroke substructures is defined using the consistent stroke connection relations. A knowledge guided recognition process is employed to identify the types of the extracted basic stroke substructures found in a handwritten character. Then a 1-D character coding scheme is given to represent the character and the code can be also used for character preclassification.
12341856
Similarity spreading: a unified framework for similarity calculation of interrelated objects
In many Web search applications, similarities between objects of one type (say, queries) can be affected by the similarities between their interrelated objects of another type (say, Web pages), and vice versa. We propose a novel framework called similarity spreading to take account of the interrelationship and improve the similarity calculation. Experiment results show that the proposed framework can significantly improve the accuracy of the similarity measurement of the objects in a search engine.
15657776
Link fusion: a unified link analysis framework for multi-type interrelated data objects
Web link analysis has proven to be a significant enhancement for quality based web search. Most existing links can be classified into two categories: intra-type links (e.g., web hyperlinks), which represent the relationship of data objects within a homogeneous data type (web pages), and inter-type links (e.g., user browsing log) which represent the relationship of data objects across different data types (users and web pages). Unfortunately, most link analysis research only considers one type of link. In this paper, we propose a unified link analysis framework, called "link fusion", which considers both the inter- and intra- type link structure among multiple-type inter-related data objects and brings order to objects in each data type at the same time. The PageRank and HITS algorithms are shown to be special cases of our unified link analysis framework. Experiments on an instantiation of the framework that makes use of the user data and web pages extracted from a proxy log show that our proposed algorithm could improve the search effectiveness over the HITS and DirectHit algorithms by 24.6% and 38.2% respectively.
1486827
User Access Pattern Enhanced Small Web Search
Current search engines generally employ link analysis techniques to web-page re-ranking. However, the same techniques are problematic in small webs, such as websites or intranet webs, because the link structure is different from the global Web. We propose a re-ranking mechanism based on implicit links generated from user access patterns. Experimental results indicate that our method outperforms keyword-based method, explicit link-based PageRank and DirectHit.