OpenRaiser/Intern-Atlas huggingface dataset:
n23Tool: a Tool for Exploring Large Relational Data Sets Through 3D Dynamic Projections
Authors: Li Yang
Venue: CIKM
Year: 2000

Visual exploration of large relational datasets is always a challenge for exploratory analysis and has immediate applications in data mining, information classification and information retrieval. n23Tool is a tool designed for interactive exploratory visualization of large relational datasets and data clusters. It employs the grand tour method to view multidimensional data through 3D dynamic projections. A 3D cluster-guided tour could be designed to display data clusters where path of the tour is determined by cluster centroids. The cluster-guided tour makes inter-clusterdistance-preserving projections in the perspectives that clusters are displayed as separate as possible. n23Tool supports the visualization of very large relational datasets by using volume rendering through texture splatting. Only aggregations or parts of data needed for rendering are retrieved from databases. n23Tool can process continuous variables as well as categorical variables. This approach of multidimensional visualization provides a natural metaphor to visualize large datasets and data clusters by mapping the data onto a timeindexed family of 3D linear projections suitable for human eye's exploration.
A Framework for Designing Update Objects to Improve Server Scalability in Intermittently Synchronized Databases
Authors: Wai Gen Yee, Michael J. Donahoo, Shamkant B. Navathe
Venue: CIKM
Year: 2000

Article Free Access Share on A framework for designing update objects to improve server scalability in intermittently synchronized databases Authors: Wai Gen Yee College of Computing, Georgia Institute of Technology, 801 Atlantic Drive, Atlanta, GA College of Computing, Georgia Institute of Technology, 801 Atlantic Drive, Atlanta, GAView Profile , Michael J. Donahoo Baylor University, P.O. Box 97356, Waco, TX Baylor University, P.O. Box 97356, Waco, TXView Profile , Shamkant B. Navathe College of Computing, Georgia Institute of Technology, 801 Atlantic Drive, Atlanta, GA College of Computing, Georgia Institute of Technology, 801 Atlantic Drive, Atlanta, GAView Profile Authors Info & Claims CIKM '00: Proceedings of the ninth international conference on Information and knowledge managementNovember 2000 Pages 54–61https://doi.org/10.1145/354756.354787Published:06 November 2000Publication History 4citation388DownloadsMetricsTotal Citations4Total Downloads388Last 12 Months16Last 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 SiteeReaderPDF
The Webspace Method: On the Integration of Database Technology with Multimedia Retrieval
Authors: Roelof van Zwol, Peter M. G. Apers
Venue: CIKM
Year: 2000

Large collections of documents containing various types of multimedia, are made available to the WWW. Unfortunately, due to the un-structuredness of Internet environments it is hard to find specific information when one is looking for it. Search engines available can only rely their results on information retrieval techniques and most of the time they lack the desired power in query formulation. Modelling data on the web, as if it was designed for use within databases, should provide us with the necessary basis for enhancing this query formulation. This of course requires special care for dealing with the included multimedia data and the semi-structured aspects of data on the web. Modelling the entire web would be too ambitious, therefore we focus on a more feasible environment, like the intranet, where one can find large collections of related data. With the webspace method we have already shown how to deal with the various aspects of semi-structured data in large collections of related documents. In this paper we focus on the integration of our webspace method for concept-based search with content-based multimedia information retrieval (IR). A webspace consists of two levels. At the document level, a webspace is considered to be a collection of related documents. At the semantical level, concepts are defined to be used in the documents at the document level. By modelling these concepts using a webspace schema a semantical level of abstraction is gained. This supplies the necessary platform for querying data available within a specific webspace. For the integration with content-based information retrieval an existing IR model is adopted. We will discuss how this is used in the context of Mirror, a Multimedia DBMS, and how this framework is used for the integration with the webspace method for concept-based search.
Combining Multiple Classifiers for Text Categorization
Authors: Khalid Al-Kofahi, Alex Tyrrell, Arun Vachher, Tim Travers, Peter Jackson
Venue: CIKM
Year: 2001

A major problem facing online information services is how to index and supplement large document collections with respect to a rich set of categories. We focus upon the routing of case law summaries to various secondary law volumes in which they should be cited. Given the large number (> 13,000) of closely related categories, this is a challenging task that is unlikely to succumb to a single algorithmic solution. Our fully implemented and recently deployed system shows that a superior classification engine for this task can be constructed from a combination of classifiers. The multi-classifier approach helps us leverage all the relevant textual features and meta data, and appears to generalize to related classification tasks.
Effective Arabic-English Cross-Language Information Retrieval via Machine-Readable Dictionaries and Machine Translation
Authors: Mohammed Aljlayl, Ophir Frieder
Venue: CIKM
Year: 2001

In Cross-Language Information Retrieval (CLIR), queries in one language retrieve relevant documents in other languages Machine-Readable Dictionary (MRD) and Machine Translation (MT) are important resources for query translation in CLIR. We investigate MT and MRD to Arabic-English CLIR. The translation ambiguity associated with these resources is the key problem. We present three methods of query translation using a bilingual dictionary for Arabic-English CLIR. First, we present the Every-Match (EM) method. This method yields ambiguous translations since many extraneous terms are added to the original query. To disambiguate the query translation, we present the First-Match (FM) method that considers the first match in the dictionary as the candidate term. Finally, we present the Two-Phase (TP) method. We show that good retrieval effectiveness can be achieved without complex resources using the Two-Phase method for Arabic-English CLIR. We also empirically evaluate the effectiveness of the MT-based method using short, medium, and long queries from TREC. The effects of the query length on the quality of the MT-based CLIR are investigated.
Extracting Meaningful Labels for WEBSOM Text Archives
Authors: Arnulfo P. Azcarraga, Teddy N. Yap Jr.
Venue: CIKM
Year: 2001

Self-Organizing Maps, being used mainly with data that are not pre-labeled, need automatic procedures for extracting keywords as labels for each of the map units. The WEBSOM methodology for building very large text archives has a very slow method for extracting such unit labels. It computes the relative frequencies of all the words of all the documents associated to each unit and then compares these to the relative frequencies of all the words of all the other units of the map. Since maps may have more than 100,000 units and the archive may contain up to 7 million documents, the existing WEBSOM method is not practical. This paper describes how the meaningful labels per map unit can be deduced by analyzing the relative weight distribution of the SOM weight vectors and by taking advantage of some characteristics of the random projection method used in dimensionality reduction. The effectiveness of this technique is demonstrated on archives of the well studied Reuters and CNN collections. Comparisons with the WEBSOM method are provided.
Structural Proximity Searching for Large Collections of Semi-Structured Data
Authors: Michael Barg, Raymond K. Wong
Venue: CIKM
Year: 2001

The richness of the XML data format allows data to be structured in a way which precisely captures the semantics required by the author. It is the structure of the data, however, which forms the basis of all XML query languages. Without at least some notion of the structure, a user cannot meaningfully query the data. This problem is compounded when one considers that heterogeneous data adhering to different schema are likely to exist in the database(s) being queried. This paper proposes a solution based on an efficient proximity index. In particular, we describe a family of encoding and compression schemes which enable us to build an index to efficiently implement the proximity search. Our index is extremely small, and can reflect updates in the underlying database in modest time. Experiments show that our algorithm and implementation are fast and scale well.
Real Time User Context Modeling for Information Retrieval Agents
Authors: Travis Bauer, David B. Leake
Venue: CIKM
Year: 2001

The success of personal information agents depends on their ability to provide task-relevant information. This paper presents WordSieve, a new algorithm that generates context descriptions to guide document indexing and retrieval. WordSieve exploits information about the sequence of accessed documents to identify words which indicate a shift in context. We have tested WordSieve in a personal information agent, Calvin, which monitors a user's document access, generates a representation of the user's task context, indexes the resources consulted, and presents recommendations for other resources that were consulted in similar prior contexts. In initial experiments, WordSieve outperforms term frequency/inverse document frequency at matching documents to hand-coded vector representations of the task contexts in which they were originally consulted, where the task context representations are term vectors representing a specific search task given to the user.
Information Access in Implicit Culture Framework
Authors: Enrico Blanzieri, Paolo Giorgini, Paolo Massa, Sabrina Recla
Venue: CIKM
Year: 2001

The goal of a System for Implicit Culture Support (SICS) is to establish an implicit culture phenomenon, namely when the elements of a set behave according to the culture of a generally different group of agents. Earlier work claimed that Implicit Culture support can be seen as a generalization of Collaborative Filtering. In this paper, we recall the concept of Implicit Culture, show how it is useful for automatically exploit tacit knowledge and we present an implementation of a System for Implicit Culture Support.
Predicting the Cost-Quality Trade-Off for Information Retrieval Queries: Facilitating Database Design and Query Optimization
Authors: Henk Ernst Blok, Djoerd Hiemstra, Sunil Choenni, Franciska de Jong, Henk M. Blanken, Peter M. G. Apers
Venue: CIKM
Year: 2001

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X007: Applying 007 Benchmark to XML Query Processing Tool
Authors: Stéphane Bressan, Gillian Dobbie, Zoé Lacroix, Mong-Li Lee, Ying Guang Li, Ullas Nambiar, Bimlesh Wadhwa
Venue: CIKM
Year: 2001

If XML is to play the critical role of the lingua franca for Internet data interchange that many predict, it is necessary to start designing and adopting benchmarks allowing the comparative performance analysis of the tools being developed and proposed. The effectiveness of existing XML query languages has been studied by many, with a focus on the comparison of linguistic features, implicitly reflecting the fact that most XML tools exist only on paper. In this paper, with a focus on efficiency and concreteness, we propose a pragmatic first step toward the systematic benchmarking of XML query processing platforms with an initial focus on the data (versus document) point of view. We propose XOO7, an XML version of the OO7 benchmark. We discuss the applicability of XOO7, its strengths, limitations and the extensions we are considering. We illustrate its use by presenting and discussing the performance comparison against XOO7 of three different query processing platforms for XML.
Towards Speech as a Knowledge Resource
Authors: Eric W. Brown, Savitha Srinivasan, Anni Coden, Dulce B. Ponceleon, James W. Cooper, Arnon Amir, Jan Pieper
Venue: CIKM
Year: 2001

Speech is a tantalizing mode of human communication. On the one hand, humans understand speech with ease and use speech to express complex ideas, information, and knowledge. On the other hand, automatic speech recognition with computers is still very hard, and extracting knowledge from speech is even harder. In this paper we motivate the study of speech as a knowledge resource and briefly survey a family of related applications and systems being developed at IBM Research aimed towards the goal of exploiting speech as a knowledge resource.
Faciliating Knowledge Flow through the Enterprise
Authors: Jeanette Bruno
Venue: CIKM
Year: 2001

This paper is concerned with the issues we encountered when attempting to achieve enterprise level knowledge reuse. We present 3 pilot studies where new visualization techniques were used to allow manufacturing and service operations take advantage of engineering knowledge embodied in 3D models. Though all these studies showed dramatic productivity increases, only one business unit from the studies is currently working to achieve the reuse. There are a number of reasons why this is so, but the key underlying theme is a lack of enterprise level commitment to knowledge sharing and a lack of an adequate knowledge architecture for sharing knowledge across organizational boundaries. We conclude with an approach for facilitating knowledge flow across functional units.
Automatic Query Expansion Based on Divergence
Authors: D. Cai, C. J. van Rijsbergen, Joemon M. Jose
Venue: CIKM
Year: 2001

In this paper we are mainly concerned with discussion of a formal model, based on the basic concept of divergence from information theory, for automatic query expansion. The basic principles and ideas on which our study is based are described. A theoretical framework is established, which allows the comparison and evaluation of different term scoring functions for identifying good terms for query expansion. The approaches proposed in this paper have been implemented and evaluated on collections from TREC. Preliminary results show that our approaches are viable and worthy of continued investigation.
Dynamic and Hierarchical Spatial Access Method using Integer Searching
Authors: Kyoosang Cho, Yijie Han, Yugyung Lee, E. K. Park
Venue: CIKM
Year: 2001

Dynamic and complex computation in the area of Geographic Information System (GIS) or Mobile Computing System involves huge amount of spatial objects such as points, boxes, polygons, etc and requires a scalable data structure and an efficient management tool for this information. In this paper, for a dynamic management of spatial objects, we construct a hierarchical dynamic data structure, called an IST/OPG hierarchy, which may overcome some limitations of existing Spatial Access Methods (SAMs). The hierarchy is constructed by combining three primary components: (1) Minimum Boundary Rectangle (MBR), which is the most widely used method among SAMs; (2) the population-based domain slicing, which is modified from the Grid File [14]; (3) extended optimal Integer Searching algorithm [4]. For dynamic management of spatial objects in the IST/OPG hierarchy, a number of primary and supplementary operations are introduced. This paper includes a comparative analysis of our approach with previous SAMs, such as R-Tree, R+-Tree and R*-Tree and QSF-Tree. The results of analysis show that our approach is better than other SAMs in construction and query time and space requirements. Specifically, for a given search domain with n objects, our query operations yield $O($ \scriptsize $\sqrt {\frac {\log n} {\log\log n}}$\normalsize $)$ compared to $O(\log n)$ of the fast SAM and an IST/OPG hierarchy containing $n$ objects can be constructed in $O(n$ \scriptsize $\sqrt {\frac {\log n}{\log\log n}}$\normalsize $)$ time and O(n) space.
Automatic Recognition of Distinguishing Negative Indirect History Language in Judicial Opinions
Authors: Jack G. Conrad, Daniel P. Dabney
Venue: CIKM
Year: 2001

We describe a model-based filtering application that generates candidate case-to-case distinguishing citations. We developed the system to aid editors in identifying indirect relationships among judicial opinions in a database of over 5 million documents. Using a training collection of approximately 30,000 previously edited cases, the filter application provides ranked sets of textual evidence for current case law documents in the editorial process. These sets contain judicial language with a strong probability of containing distinguishing relationships. Integrating this application into the editorial review environment has greatly improved the coverage and efficiency of the work flow to identify and generate new distinguishing relationship entries.
Rapid Association Rule Mining
Authors: Amitabha Das, Wee Keong Ng, Yew Kwong Woon
Venue: CIKM
Year: 2001

Association rule mining is a well-researched area where many algorithms have been proposed to improve the speed of mining. In this paper, we propose an innovative algorithm called Rapid Association Rule Mining (RARM) to once again break this speed barrier. It uses a versatile tree structure known as the Support-Ordered Trie Itemset (SOTrieIT) structure to hold pre-processed transactional data. This allows RARM to generate large 1-itemsets and 2-itemsets quickly without scanning the database and without candidate 2-itemset generation. It achieves significant speed-ups because the main bottleneck in association rule mining using the Apriori property is the generation of candidate 2-itemsets. RARM has been compared with the classical mining algorithm Apriori and it is found that it outperforms Apriori by up to two orders of magnitude (100 times), much more than what recent mining algorithms are able to achieve.
Alternative Representations and Abstractions for Moving Sensors Databases
Authors: Jacob Eisenstein, Shahram Ghandeharizadeh, Cyrus Shahabi, Gautam Shanbhag, Roger Zimmermann
Venue: CIKM
Year: 2001

Moving sensors refers to an emerging class of data intensive applications that inpacts disciplines such as communication, health-care, scientific applications, etc. These applications consist of a fixed number of sensors that move and produce streams of data as a function of time. They may require the system to match these streams against stored streams to retrieve relevant data (patterns). With communication, for example, a speaking impaired individual might utilize a haptic glove that translates hand signs into written (spoken) words. The glove consists of sensors for different finger joints. These sensors report their location and values as a function of time, producing streams of data. These streams are matched against a repository of spatio-temporal streams to retrieve the corresponding English character or word.The contributions of this study are two fold. First, it introduces a framework to store and retrieve "moving sensors" data. The framework advocates physical data independence and software-reuse. Second, we investigate alternative representations for storage and retrieve of data in support of query processing. We quantify the tradeoff associated with these alternatives using empirical data RoboCup soccer matches.
Summarization of Discussion Groups
Authors: Robert G. Farrell, Peter G. Fairweather, Kathleen Snyder
Venue: CIKM
Year: 2001

In this paper, we describe an algorithm to generate textual summaries of discussion groups. Our system combines sentences extracted from individual postings into variable-length summaries by utilizing the hierarchical discourse context provided by discussion threads. We have incorporated this algorithm into a Web-based application called IDS (Interactive Discussion Summarizer).
A Domain Independent Environment for Creating Information Extraction Modules
Authors: Ronen Feldman, Yonatan Aumann, Yair Liberzon, Kfir Ankori, Yonatan Schler, Binyamin Rosenfeld
Venue: CIKM
Year: 2001

Text-Mining is a growing area of interest within the field of Data Mining and Knowledge Discovery. Given a collection of text documents, most approaches to Text Mining perform knowledgediscovery operations either on external tags associated with each document, or on the set of all words within each document. Both approaches suffer from limitations. This paper focuses on an intermediate approach, one that we call text mining via information extraction, in which knowledge discovery takes place on focused, relevant terms, phrases and facts, as extracted from the documents.
Efficient Processing of Conical Queries
Authors: Hakan Ferhatosmanoglu, Divyakant Agrawal, Amr El Abbadi
Venue: CIKM
Year: 2001

Conical queries are a novel type of query with an increasing number of applications. Traditional index structures and retrieval mechanisms, in general, have been optimized for rectangular and circular queries, rather than conical queries. In this paper, we focus on conical queries which can be defined as a multi-dimensional cone in a multi-dimensional data space. We develop a model for expressing such queries and suggest efficient techniques for evaluating them. In particular, we explore the retrieval problem in the context of conical query processing and develop multi-disk allocation methods specifically for processing conical queries.
Approximately Common Patterns in Shared-Forests
Authors: Manuel Vilares Ferro, Francisco J. Ribadas, Jorge Graña Gil
Venue: CIKM
Year: 2001

We present a proposal intended to demonstrate the applicability of tabulation techniques for detecting approximately common patterns when dealing with structures sharing some common parts. This sharing saves on the space needed to represent the structures and also on their later processing, by factorizing the filtering of substructure matching. As a consequence, preliminary experimental tests indicate a reduction of the running time.
Tempus Fugit: A System for Making Semantic Connections
Authors: Daniel Alexander Ford, Joann Ruvolo, Stefan Edlund, Jussi Myllymaki, James H. Kaufman, Jared Jackson, Martin Gerlach
Venue: CIKM
Year: 2001

Tempus Fugit (Time Flies) is the first of a new generation of Personal Information Management (PIM) systems. A PIM system incorporates an electronic calendar, list and address book. The premise behind Tempus Fugit is that information stored in electronic calendars, to-do lists and address books can be given richer semantic interpretation and automatically processed to make its users more effective. Tempus Fugit also tracks the physical and virtual locations of users and uses this information to predict meeting attendance and help them as they travel during their day.