35937629
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 new data structures. We present both theoretical and empirical analysis of the algorithms and prove that both algorithms have optimal time complexity.
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.
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.
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
5754331
Web-page summarization using clickthrough data
Most previous Web-page summarization methods treat a Web page as plain text. However, such methods fail to uncover the full knowledge associated with a Web page needed in building a high-quality summary, because many of these methods do not consider the hidden relationships in the Web. Uncovering the hidden knowledge is important in building good Web-page summarizers. In this paper, we extract the extra knowledge from the clickthrough data of a Web search engine to improve Web-page summarization. Wefirst analyze the feasibility in utilizing the clickthrough data to enhance Web-page summarization and then propose two adapted summarization methods that take advantage of the relationships discovered from the clickthrough data. For those pages that are not covered by the clickthrough data, we design a thematic lexicon approach to generate implicit knowledge for them. Our methods are evaluated on a dataset consisting of manually annotated pages as well as a large dataset that is crawled from the Open Directory Project website. The experimental results indicate that significant improvements can be achieved through our proposed summarizer as compared to the summarizers that do not use the clickthrough data.
207643
User Modeling for Efficient Use of Multimedia Files
It is very common that a user likes to collect many multimedia files of their interests from the web or other sources for his/her daily use, such as in emails, presentations, and technical documents. This paper presents algorithms to learn user models, in particular, user intention models and preference models from the usage of these files. Such usages include downloading, inserting, and sending multimedia files. A user intention model predicts when the user may want to involve some multimedia objects in his currently working environment (e.g., an email) and provides more convenient and accurate help to the user. A user preference model describes the types and classes of the user's favorite multimedia files and helps an offline crawler to autonomously collect more useful multimedia files for the user. The algorithms have been implemented in our media agents system and shown their effectiveness in user modeling.
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.
16272457
SimFusion: measuring similarity using unified relationship matrix
In this paper we use a Unified Relationship Matrix (URM) to represent a set of heterogeneous data objects (e.g., web pages, queries) and their interrelationships (e.g., hyperlinks, user click-through sequences). We claim that iterative computations over the URM can help overcome the data sparseness problem and detect latent relationships among heterogeneous data objects, thus, can improve the quality of information applications that require com- bination of information from heterogeneous sources. To support our claim, we present a unified similarity-calculating algorithm, SimFusion. By iteratively computing over the URM, SimFusion can effectively integrate relationships from heterogeneous sources when measuring the similarity of two data objects. Experiments based on a web search engine query log and a web page collection demonstrate that SimFusion can improve similarity measurement of web objects over both traditional content based algorithms and the cutting edge SimRank algorithm.
17657159
A Chinese-character thinning algorithm based on global features and contour information
This paper proposes a method of using run-length coding to perform thinning. First, we construct graphs from characters. The attributes (vertical lines, horizontal lines or points) of each node in the graph are determined according to the node's relationship to the nodes above and below it (we will refer to these relationships as global features) and the black runs within the node. Intersections between two adjacent segments are determined on the basis of the graph constructed and contour information. The thinning algorithm thus employs global features and contour information to produce a more accurate skeleton.