OpenRaiser/Intern-Atlas huggingface dataset:
A Visual Tool for Structuring and Modeling Organizational Memories
Authors: Tang-Ho Lê, Luc Lamontagne, Tho-Hau Nguyen
Venue: CIKM
Year: 2000

Article A visual tool for structuring and modeling organizational memories Share on Authors: Tang-Ho Lê University of Moncton, Computer Science Department, Moncton (NB) Canada E1A 3E9 University of Moncton, Computer Science Department, Moncton (NB) Canada E1A 3E9View Profile , Luc Lamontagne Defence Research Establ. Valcartier 2459 Blvd Pie-XI north, Val-Bélair (Qc), Canada G3J 1X5 Defence Research Establ. Valcartier 2459 Blvd Pie-XI north, Val-Bélair (Qc), Canada G3J 1X5View Profile , Tho-Hau Nguyen Univ. du Québec à Montréal, CP. 8888, succ. Centre-Ville, Montreal (Qc), Canada H3C 3P8 Univ. du Québec à Montréal, CP. 8888, succ. Centre-Ville, Montreal (Qc), Canada H3C 3P8View Profile Authors Info & Claims CIKM '00: Proceedings of the ninth international conference on Information and knowledge managementNovember 2000 Pages 258–263https://doi.org/10.1145/354756.354827Online:06 November 2000Publication History 1citation541DownloadsMetricsTotal Citations1Total Downloads541Last 12 Months3Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Structural Join Index Driven Complex Object Retrieval: Mechanisms and Selection
Authors: Qing Li, Chi-Wai Fung, Kamalakar Karlapalem
Venue: CIKM
Year: 2000

ABSTRACT In this paper, we introduce structural join index hierarchy (SJIH)mechanisms that mimic the class composition hierarchy of thecomplex objects to provide direct access to complex objects and/ortheir component objects. SJIH extends the work on join index hier-archies by providing efficient and flexible access to complexobjects, thus unifying various previous indexing methods proposedfor object oriented database (OODB). A cost model for processingthe queries and maintaining the indices is developed. A heuristicalgorithm is designed to select appropriate indices to efficientlyprocess a given set of queries. We show that SJIH indexing mech-anisms facilitate efficient retrieval of complex objects. Given a setof queries and a limited index storage space, the heuristic algo-rithm facilitates fast selection of near-optimal set of indices forefficiently executing the queries. Categories and Subject Descriptors H.3.1 [Information Storage and Retrieval]: Content Analysisand Indexing -- indexing methods.
Discovery of Similarity Computations of Search Engines
Authors: King-Lup Liu, Weiyi Meng, Clement T. Yu, Naphtali Rishe
Venue: CIKM
Year: 2000

Two typical situations in which it is of practical interest to determine the similarities of text documents to a query due to a search engine are: (1) a global search engine, constructed on top of a group of local search engines, wishes to retrieve the set of local documents globally most similar to a given query; and (2) an organization wants to compare the retrieval performance of search engines. The dot-product function is a widely used similarity function. For a search engine using such a function, we can determine its similarity computations if how the search engine sets the weights of terms is known, which is usually not the case. In this paper, techniques are presented to discover certain mathematical expressions of these formulas and the values of embedded constants when the dot-product similarity function is used. Preliminary results from experiments on the WebCrawler search engine are given to illustrate our techniques. 1 1 Introduction Documents of interest are often found...
WebCQ: Detecting and Delivering Information Changes on the Web
Authors: Ling Liu, Calton Pu, Wei Tang
Venue: CIKM
Year: 2000

WebCQ is a prototype system for large-scale Web information monitoring and delivery. It makes heavy use of the structure present i n h ypertext and the concept of continual queries. In this paper we discuss both mechanisms that We-bCQ uses to discover and detect changes to the World Wide Web (the Web) pages e ciently, and the methods to notify users of interesting changes with a personalized customization. The WebCQ system consists of four main components: a c hange detection robot that discovers and detects changes, a proxy cache service that reduces communication tra cs to the original information servers, a personalized presentation tool that highlights changes detected by W ebCQ sentinels, and a change noti cation service that delivers fresh information to the right users at the right time. A salient feature of our change detection robot is its ability to support various types of web page sentinels for detecting, presenting, and delivering interesting changes to web pages. This paper describes the WebCQ system with an emphasis on general issues in designing and engineering a large-scale information change monitoring system on the Web.
Maintaining Views in Object-relational Databases
Authors: Jixue Liu, Millist W. Vincent, Mukesh K. Mohania
Venue: CIKM
Year: 2000

Article Maintaining views in object-relational databases Share on Authors: Jixue Liu School of Computer Science, University. of South Australia, Adelaide, SA5084, Australia School of Computer Science, University. of South Australia, Adelaide, SA5084, AustraliaView Profile , Millist Vincent School of Computer Science, University. of South Australia, Adelaide, SA5084, Australia School of Computer Science, University. of South Australia, Adelaide, SA5084, AustraliaView Profile , Mukesh Mohania Dept. of Computer Science, Western Michigan University, Kalamazoo, MI Dept. of Computer Science, Western Michigan University, Kalamazoo, MIView Profile Authors Info & Claims CIKM '00: Proceedings of the ninth international conference on Information and knowledge managementNovember 2000 Pages 102–109https://doi.org/10.1145/354756.354807Online:06 November 2000Publication History 6citation482DownloadsMetricsTotal Citations6Total Downloads482Last 12 Months5Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Clustering Through Decision Tree Construction
Authors: Bing Liu, Yiyuan Xia, Philip S. Yu
Venue: CIKM
Year: 2000

Clustering aims to find the intrinsic structure of data by organizing data objects into similarity groups or clusters. It is often called unsupervised learning as no class labels denoting an a priori partition of the objects are given. This is in contrast with supervised learning (e.g., classification) for which the data objects are already labeled with known classes. Past research in clustering has produced many algorithms. However, these algorithms have some major shortcomings. In this paper, we propose a novel clustering technique, which is based on a supervised learning technique called decision tree construction. The new technique is able to overcome many of these shortcomings. The key idea is to use a decision tree to partition the data space into cluster and empty (sparse) regions at different levels of details. The technique is able to find "natural" clusters in large high dimensional spaces efficiently. It is suitable for clustering in the full dimensional space as well as in subspaces. It also provides comprehensible descriptions of clusters. Experiment results on both synthetic data and real-life data show that the technique is effective and also scales well for large high dimensional datasets.
Index Interpolation: An Approach to Subsequence Matching Supporting Normalization Transform in Time-Series Databases
Authors: Woong-Kee Loh, Sang-Wook Kim, Kyu-Young Whang
Venue: CIKM
Year: 2000

In this paper, w epropose a subsequence matching algorithm that supports normalization transform in timeseries databases. Normalization transform enables nding sequences with similar uctuation patterns although they are not close to each other before the normalization transform. Application of the existing whole matching algorithm supporting normalization transform to the subsequence matching is feasible, but requires an index for ev ery possible length of the query sequence causing serious overhead on both storage space and update time. The proposed algorithm generates indexes only for a small number of di erent lengths of query sequences. F or subsequence matching it selects the most appropriate index among them. We can obtain better searc h performance by using more indexes. We c a l l o u r approach index interp olation. We formally pro ve t h a t the proposed algorithm does not cause false dismissal. F or performance evaluation, we h a ve conducted experiments using the indexes for only ve di erent lengths out of the lengths 256 512 of the query sequence. The results show that the proposed algorithm outperforms the sequential scan by up to 14.6 times on the average when the selectivity of the query is 10 ;5 .
Sampling from Databases Using B+-Trees
Authors: Dimuthu Prasanna Makawita, Kian-Lee Tan, Huan Liu
Venue: CIKM
Year: 2000

Article Free Access Share on Sampling from databases using B+-trees Authors: Dimuthu Makawita Ngee Ann Polytechnic, Centre for Computer Studies, 535, Clementi Road, Singapore 599489 Ngee Ann Polytechnic, Centre for Computer Studies, 535, Clementi Road, Singapore 599489View Profile , Kian-Lee Tan School of Computing, National Univ. of Singapore, 3 Science Drive 2, Singapore 117543 School of Computing, National Univ. of Singapore, 3 Science Drive 2, Singapore 117543View Profile , Huan Liu Dept. of Comp. Sc. & Eng, Arizona State University, P.O. BOX 875406, Tempe, AZ Dept. of Comp. Sc. & Eng, Arizona State University, P.O. BOX 875406, Tempe, AZView Profile Authors Info & Claims CIKM '00: Proceedings of the ninth international conference on Information and knowledge managementNovember 2000Pages 158–164https://doi.org/10.1145/354756.354814Published:06 November 2000Publication History 1citation475DownloadsMetricsTotal Citations1Total Downloads475Last 12 Months50Last 6 weeks6 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
Scalable association-based text classification
Authors: Dimitris Meretakis, Dimitris Fragoudis, Hongjun Lu, Spiros Likothanassis
Venue: CIKM
Year: 2000

Nave Bayes (NB) classifier has long been considered a core methodology in text classification mainly due to its simplicity and computational efficiency. There is an increasing need however for methods that can achieve higher classification accuracy while maintaining the ability to process large document collections. In this paper we examine text categorization methods from a perspective that considers the tradeoff between accuracy and scalability to large data sets and large feature sizes. We start from the observation that Support Vector Machines, one of the best text categorization methods cannot scale up to handle the large document collections involved in many real word problems. We then consider bayesian extensions to NB that achieve higher accuracy by relaxing its strong independence assumptions. Our experimental results show that LB, an association-based lazy classifier can achieve a good tradeoff between high classification accuracy and scalability to large document collections...
Extensible Perfect Hashing
Authors: Takao Miura, Wataru Matsumoto, Isamu Shioya, Yukio Wada
Venue: CIKM
Year: 2000

Article Free Access Share on Extensible perfect hashing Authors: Takao Miura Dept. of Elect. and Elect. Engr., Hosei University, Kajinocho, Koganei, Tokyo, Japan Dept. of Elect. and Elect. Engr., Hosei University, Kajinocho, Koganei, Tokyo, JapanView Profile , Wataru Matsumoto Dept. of Elect. and Elect. Engr., Hosei University, Kajinocho, Koganei, Tokyo, Japan Dept. of Elect. and Elect. Engr., Hosei University, Kajinocho, Koganei, Tokyo, JapanView Profile , Isamu Shioya Dept. of Informatics, SANNO University, Kamikasuya, Isehara, Kanagawa, Japan Dept. of Informatics, SANNO University, Kamikasuya, Isehara, Kanagawa, JapanView Profile , Yukio Wada HITACHI Software Engineering Co. Ltd., Yokohama, Kanagawa, Japan HITACHI Software Engineering Co. Ltd., Yokohama, Kanagawa, JapanView Profile Authors Info & Claims CIKM '00: Proceedings of the ninth international conference on Information and knowledge managementNovember 2000 Pages 446–452https://doi.org/10.1145/354756.354852Published:06 November 2000Publication History 2citation298DownloadsMetricsTotal Citations2Total Downloads298Last 12 Months12Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
Object and Query Transformation: Supporting Multi-Dimensional Queries through Code Reuse
Authors: Ratko Orlandic, Byunggu Yu
Venue: CIKM
Year: 2000

Article Object and query transformation: supporting multi-dimensional queries through code reuse Share on Authors: Byunggu Yu University of Wyoming, Department of Computer Science, PO Box 3682, Laramie, WY University of Wyoming, Department of Computer Science, PO Box 3682, Laramie, WYView Profile , Ratko Orlandic Illinois Institute of Technology, Department of Computer Science, 10 West 31st Street, Chicago, IL Illinois Institute of Technology, Department of Computer Science, 10 West 31st Street, Chicago, ILView Profile Authors Info & Claims CIKM '00: Proceedings of the ninth international conference on Information and knowledge managementNovember 2000 Pages 141–149https://doi.org/10.1145/354756.354812Published:06 November 2000 1citation767DownloadsMetricsTotal Citations1Total Downloads767Last 12 Months2Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Extending OLAP Querying to External Object Databases
Authors: Torben Bach Pedersen, Arie Shoshani, Junmin Gu, Christian S. Jensen
Venue: CIKM
Year: 2000

On-Line Analytical Processing (OLAP) systems based on a multidimensional view of data have found widespread use in business applications and are being used increasingly in non-standard applications. These systems provide good performance and ease-of-use. However, the complex structures and relationships inherent in data in non-standard applications are not accommodated well by OLAP systems. In contrast, object database systems are built to handle such complexity, but do not support OLAP-type querying well.
The Subspace Coding Method: A New Indexing Scheme for High-Dimensional Data
Authors: Yasushi Sakurai, Masatoshi Yoshikawa, Shunsuke Uemura, Haruhiko Kojima
Venue: CIKM
Year: 2000

This paper presents a new indexing scheme, the Subspace Coding Method (SCM), that offers high performance similarity retrieval. It is based on an analysis of the two superior access methods proposed so far: the SR-tree and the VAFile. Our experimental test by real data provides that the SR-tree offers better performance. However, as dimensionality increases, the large volume of entries in non-leaf nodes degrades the search performance. Based on the analysis, we introduce the SCM, a new indexing scheme applicable to any tree index employing MBR (Minimum Bounding Rectangle) and/or MBS (Minimum Bounding Sphere). The basic idea of the SCM is the introduction of Virtual Bounding Rectangle (VBR) and Virtual Bounding quasiSphere (VBS), which contain and approximate MBR and MBS, respectively. Unlike the approximation of absolute vector positions used in the VA-File, VBRs and VBSs are relative to the parent’s VBR. The experimental results demonstrate the effectiveness of the SCM.
Polar: An Architecture for a Parallel ODMG Compliant Object Database
Authors: Jim Smith, Paul Watson, Sandra de F. Mendes Sampaio, Norman W. Paton
Venue: CIKM
Year: 2000

Article Polar: an architecture for a parallel ODMG compliant object database Share on Authors: Jim Smith Department of Computing Science, University of Newcastle upon Tyne, Newcastle upon Tyne, NE1 7RU UK Department of Computing Science, University of Newcastle upon Tyne, Newcastle upon Tyne, NE1 7RU UKView Profile , Paul Watson Department of Computing Science, University of Newcastle upon Tyne, Newcastle upon Tyne, NE1 7RU UK Department of Computing Science, University of Newcastle upon Tyne, Newcastle upon Tyne, NE1 7RU UKView Profile , Sandra de F. Mendes Sampaio Department of Computing Science, University of Manchester, Oxford Road, Manchester, M13 9PL UK Department of Computing Science, University of Manchester, Oxford Road, Manchester, M13 9PL UKView Profile , Norman Paton Department of Computing Science, University of Manchester, Oxford Road, Manchester, M13 9PL UK Department of Computing Science, University of Manchester, Oxford Road, Manchester, M13 9PL UKView Profile Authors Info & Claims CIKM '00: Proceedings of the ninth international conference on Information and knowledge managementNovember 2000 Pages 352–359https://doi.org/10.1145/354756.354840Online:06 November 2000Publication History 12citation401DownloadsMetricsTotal Citations12Total Downloads401Last 12 Months3Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Visual Query and Analysis Tool of the Object-Relational GIS Framework
Authors: Zoran Stojanovic, Slobodanka Djordjevic-Kajan, Dragan Stojanovic
Venue: CIKM
Year: 2000

Article Visual query and analysis tool of the object-relational GIS framework Share on Authors: Zoran Stojanovic Computer Science Department, Faculty of Electronic Engineering, University of Nis, Beogradska 14, 18000 Nis, Yugoslavia Computer Science Department, Faculty of Electronic Engineering, University of Nis, Beogradska 14, 18000 Nis, YugoslaviaView Profile , Slobodanka Djordjevic-Kajan View Profile , Dragan Stojanovic View Profile Authors Info & Claims CIKM '00: Proceedings of the ninth international conference on Information and knowledge managementNovember 2000 Pages 328–335https://doi.org/10.1145/354756.354836Online:06 November 2000Publication History 1citation1,054DownloadsMetricsTotal Citations1Total Downloads1,054Last 12 Months4Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Supporting Subseries Nearest Neighbor Search via Approximation
Authors: Changzhou Wang, Xiaoyang Sean Wang
Venue: CIKM
Year: 2000

1. INTRODUCTION Searching for nearest neighbors among a large number of time series is an important data mining task in many application domains varying from economics to physics to experimental science in general. Time series are usually modeled as high-dimensional points and proximity of time series is often measured by some metric distance function on their corresponding points [12, 10, 4]. Depending on application needs, time series nearest neighbor searches may be classified into three categories: Whole series query Given a query series and a positive
Semantic Search on Internet Tabular Information Extraction for Answering Queries
Authors: Huei-Long Wang, Shih-Hung Wu, K. K. Wang, Cheng-Lung Sung, Wen-Lian Hsu, Wei-Kuan Shih
Venue: CIKM
Year: 2000

Although extracting information from tables is essential for Internet information agents, most tables are designed for human eyes and their layout and semantic meanings are not well defined. In practice, encoding the layout of each information source is impossible. This work presents a novel semantic search approach capable of extracting information from general tables. Semantic ontology allows our agents to read tables in the same knowledge domain with different layouts. In addition, a system of layout syntax and a set of transformation rules are defined to transform tables into databases without losing their semantic meanings.
Using Wavelet Decomposition to Support Progressive and Approximate Range-Sum Queries over Data Cubes
Authors: Yi-Leh Wu, Divyakant Agrawal, Amr El Abbadi
Venue: CIKM
Year: 2000

Data cubes are designed to pro vide aggregate information that can be used to analyze the contents of databases and data w arehouses. A range query applies an aggregation operation (e.g., SUM, A VERAGE) over all selected cells in a data cube, where the selection is speci ed by providing ranges of values on di erent dimensions. Previous approaches to process the range sum query on data cubes (e.g., pre x sum) have l o w query costs but have high update costs. We use the discrete wavelet transformation to decompose a data cube into w avelet coe cien ts of di erent resolutions. The resulting decomposed data cube can be used for progressiv eand appro ximatequery processing. This new approach can handle clustered and sparse data gracefully and can provide e cient performance for both queries and updates, which m a k es the wavelet decomposition technique suitable for dynamic data cube environments.
A Comparison of DFT and DWT based Similarity Search in Time-Series Databases
Authors: Yi-Leh Wu, Divyakant Agrawal, Amr El Abbadi
Venue: CIKM
Year: 2000

Similarity search in time-series databases has received significant attention lately. Popular techniques for efficient retrieval of time sequences in time-series databases has been to use Discrete Fourier Transform (DFT). Recently, the Discrete Wavelet Transform (DWT) has gained popular interest in database domain and several proposals have been made to replace DFT by DWT for similarity search over time-series databases. In this paper, we explore the feasibility of replacing DFT by DWT with a comprehensive analysis of the DFT and DWT as matching functions in time-series databases. Our results show that although the DWT based technique has several advantages, e.g., the DWT has complexity of O(N) whereas DFT is O(N log N ), DWT does not reduce relative matching error and does not increase query precision in similarity search as suggested by previous works [1]. We conclude that, by exploring the conjugate property of DFT in real domain, the DFT-based and DWT-based techniques yiel...