OpenRaiser/Intern-Atlas huggingface dataset:
The role of variance in term weighting for probabilistic information retrieval
Authors: Warren R. Greiff, William T. Morgan, Jay M. Ponte
Venue: CIKM
Year: 2002

In probabilistic approaches to information retrieval, the occurrence of a query term in a document contributes to the probability that the document will be judged relevant. It is typically assumed that the weight assigned to a query term should be based on the expected value of that contribution. In this paper we show that the degree to which observable document features such as term frequencies are expected to vary is also important. By means of stochastic simulation, we show that increased variance results in degraded retrieval performance. We further show that by decreasing term weights in the presence of variance, this degradation can be reduced. Hence, probabilistic models of information retrieval must take into account not only the expected value of a query term's contribution but also the variance of document features.
The effectiveness study of various music information retrieval approaches
Authors: Jia-Lien Hsu, Arbee L. P. Chen, Hung-Chen Chen, Ning-Han Liu
Venue: CIKM
Year: 2002

In this paper, we describe the Ultima project which aims to construct a platform for evaluating various approaches of music information retrieval. Two kinds of approaches are adopted in this project. These approaches differ in various aspects, such as representations of music objects, index structures, and approximate query processing strategies. For a fair comparison, we propose a measurement of the retrieval effectiveness by recall-precision curves with a scaling factor adjustment. Finally, the performance study of the retrieval effectiveness based on various factors of these approaches is presented. Keywords music database, retrieval methods, retrieval effectiveness, evaluation platform, performance study. 1.
Comparison of interestingness functions for learning web usage patterns
Authors: Xiangji Huang, Nick Cercone, Aijun An
Venue: CIKM
Year: 2002

Livelink is a collaborative intranet, extranet and e-business application that enables employees and business partners of an organization to capture, share and reuse business information and knowledge. The usage of the Livelink software has been recorded by the Livelink Web server in its log files. We present an application of data mining techniques to the Livelink Web usage data. In particular, we focus on how to find interesting association rules and sequential patterns from the Livelink log files. A number of interestingness measures are used in our application to identify interesting rules and patterns. We present a comparison of these measures based on the feedback from domain experts. Some of the interestingness measures are found to be better than others.
An object-oriented extension of XML for autonomous web applications
Authors: Hasan M. Jamil, Giovanni A. Modica
Venue: CIKM
Year: 2002

While the idea of extending XML to include object-oriented features has been gaining popularity in general, the potential of inheritance in document design has not been well recognized in contemporary research. In this paper we demonstrate that XML with dynamic inheritance aids better document designs and decreased management overheads and support increased autonomy. As an extended application, we point out that dynamic inheritance also helps effective automated web portal and ontology designs.We present an object-oriented extension to the language of XML to include dynamic inheritance and describe a middle layer that implements our system. We explain our system with several practical examples.
Parallelizing the buckshot algorithm for efficient document clustering
Authors: Eric C. Jensen, Steven M. Beitzel, Angelo J. Pilotto, Nazli Goharian, Ophir Frieder
Venue: CIKM
Year: 2002

We present a parallel implementation of the Buckshot document clustering algorithm. We demonstrate that this parallel approach is highly efficient both in terms of load balancing and minimization of communication. In a series of experiments using the 2GB of SGML data from TReC disks 4 and 5, our parallel approach was shown to be scalable in terms of processors efficiently used and the number of clusters created.
A local search mechanism for peer-to-peer networks
Authors: Vana Kalogeraki, Dimitrios Gunopulos, Demetrios Zeinalipour-Yazti
Venue: CIKM
Year: 2002

One important problem in peer-to-peer (P2P) networks is searching and retrieving the correct information. However, existing searching mechanisms in pure peer-to-peer networks are inefficient due to the decentralized nature of such networks. We propose two mechanisms for information retrieval in pure peer-to-peer networks. The first, the modified Breadth-First Search (BFS) mechanism, is an extension of the current Gnuttela protocol, allows searching with keywords, and is designed to minimize the number of messages that are needed to search the network. The second, the Intelligent Search mechanism, uses the past behavior of the P2P network to further improve the scalability of the search procedure. In this algorithm, each peer autonomously decides which of its peers are most likely to answer a given query. The algorithm is entirely distributed, and therefore scales well with the size of the network. We implemented our mechanisms as middleware platforms. To show the advantages of our mechanisms we present experimental results using the middleware implementation.
Entropy-based link analysis for mining web informative structures
Authors: Hung-Yu Kao, Ming-Syan Chen, Shian-Hua Lin, Jan-Ming Ho
Venue: CIKM
Year: 2002

In this paper, we study the problem of mining the informative structure of a news Web site which consists of thousands of hyperlinked documents. We define the informative structure of a news Web site as a set of index pages (or referred to as TOC, i.e., table of contents, pages) and a set of article pages linked by TOC pages through informative links. It is noted that the Hyperlink Induced Topics Search (HITS) algorithm has been employed to provide a solution to analyzing authorities and hubs of pages. However, most of the content sites tend to contain some extra hyperlinks, such as navigation panels, advertisements and banners, so as to increase the add-on values of their Web pages. Therefore, due to the structure induced by these extra hyperlinks, HITS is found to be insufficient to provide a good precision in solving the problem. To remedy this, we develop an algorithm to utilize entropy-based Link Analysis on Mining Web Informative Structures. This algorithm is referred to as LAMIS. The key idea of LAMIS is to utilize information entropy for representing the knowledge that corresponds to the amount of information in a link or a page in the link analysis. Experiments on several real news Web sites show that the precision and the recall of LAMIS are much superior to those obtained by heuristic methods and conventional ink analysis methods.
Features of documents relevant to task- and fact-oriented questions
Authors: Diane Kelly, Xiaojun Yuan, Nicholas J. Belkin, Vanessa Murdock, W. Bruce Croft
Venue: CIKM
Year: 2002

We describe results from an ongoing project that considers question types and document features and their relationship to retrieval techniques. We examine eight document features from the top 25 documents retrieved from 74 questions and find that lists and FAQs occur in more documents judged relevant to task-oriented questions than those judged relevant to fact-oriented questions.
Partial rollback in object-oriented/object-relational database management systems
Authors: Won-Young Kim, Kyu-Young Whang, Byung Suk Lee, Young-Koo Lee, Ji-Woong Chang
Venue: CIKM
Year: 2002

In a database management system (DBMS), partial rollback is an important mechanism for canceling only part of the operations executed in a transaction back to a savepoint. Partial rollback complicates buffer management because it should restore the state of the buffers as well as that of the database. Several relational DBMSs (RDBMSs) currently provide this mechanism using page buffers. However, object-oriented or object-relational DBMSs (OO/ORDBMSs) cannot utilize the partial rollback scheme of RDBMSs as is because, unlike RDBMSs, many of them use a dual buffer consisting of an object buffer and a page buffer. In this paper, we propose a thorough study of partial rollback schemes of OO/ORDBMSs with a dual buffer. First, we classify the partial rollback schemes of OO/ORDBMSs into a single buffer-based scheme and a dual buffer-based scheme by the number of buffers used to process rollback. Next, we propose four alternative partial rollback schemes: a page buffer-based scheme, an object buffer-based scheme, a dual buffer-based scheme using a soft log, and a dual buffer-based scheme using shadows. We then evaluate their performance through simulations. The results show that the dual buffer-based partial rollback scheme using shadows provides the best performance. Partial rollback in OO/ORDBMS has not been addressed in the literature; yet, it is a useful mechanism that must be implemented. The proposed schemes are practical ones that can be implemented in such DBMSs.
Efficient synchronization for mobile XML data
Authors: Franky Lam, Nicole Lam, Raymond K. Wong
Venue: CIKM
Year: 2002

Many handheld applications receive data from a primary database server and operate in an intermittently connected environment these days. They maintain data consistency with data sources through sychronization. In certain applications such as sales force automation, it is highly desirable if updates on the data source can be reflected at the handheld applications immediately. This paper proposes an efficient method to synchronize XML data on multiple mobile devices. Each device retrieves and caches a local copy of data from the database source based on a regular path expression. These local copies may be overlapping or disjoint with each other. An efficient mechanism is proposed to find all the disjoint copies to avoid unnecessary synchronizations. Each update to the data source will then be checked to identify all handheld applications which are affected by the update. Communication costs can be further reduced by eliminating the forwarding of unnecessary operations to groups of mobile clients.
NeT & CoT: translating relational schemas to XML schemas using semantic constraints
Authors: Dongwon Lee, Murali Mani, Frank Chiu, Wesley W. Chu
Venue: CIKM
Year: 2002

Two algorithms, called NeT and CoT, to translate relational schemas to XML schemas using various semantic constraints are presented. The XML schema representation we use is a language-independent formalism named XSchema, that is both precise and concise. A given XSchema can be mapped to a schema in any of the existing XML schema language proposals. Our proposed algorithms have the following characteristics: (1) NeT derives a nested structure from a flat relational model by repeatedly applying the nest operator on each table so that the resulting XML schema becomes hierarchical, and (2) CoT considers not only the structure of relational schemas, but also semantic constraints such as inclusion dependencies during the translation. It takes as input a relational schema where multiple tables are interconnected through inclusion dependencies and converts it into a good XSchema. To validate our proposals, we present experimental results using both real schemas from the UCI repository and synthetic schemas from TPC-H.
Intelligent knowledge discovery in peer-to-peer file sharing
Authors: Yugyung Lee, Changgyu Oh, Eun Kyo Park
Venue: CIKM
Year: 2002

Emerging peer-to-peer computing provides new possibilities but also challenges for distributed applications. Despite their significant potential, current peer-to-peer networks lack efficient knowledge discovery and management. This paper addresses this deficiency and proposes the Intelligent File Sharing framework, which provides an effective and flexible query for P2P file sharing. The IFS is based on powerful schema and flexible inference, as well as efficiently integrated and extensible retrieval algorithms. Experimental results have provided evidence of the high performance and scalability of the Intelligent File Sharing (IFS) system in peer-to-peer environments.
XClust: clustering XML schemas for effective integration
Authors: Mong-Li Lee, Liang Huai Yang, Wynne Hsu, Xia Yang
Venue: CIKM
Year: 2002

It is increasingly important to develop scalable integration techniques for the growing number of XML data sources. A practical starting point for the integration of large numbers of Document Type Definitions (DTDs) of XML sources would be to first find clusters of DTDs that are similar in structure and semantics. Reconciling similar DTDs within such a cluster will be an easier task than reconciling DTDs that are different in structure and semantics as the latter would involve more restructuring. We introduce XClust, a novel integration strategy that involves the clustering of DTDs. A matching algorithm based on the semantics, immediate descendents and leaf-context similarity of DTD elements is developed. Our experiments to integrate real world DTDs demonstrate the effectiveness of the XClust approach.
Using micro information units for internet search
Authors: Xiaoli Li, Tong-Heng Phang, Minqing Hu, Bing Liu
Venue: CIKM
Year: 2002

Internet search is one of the most important applications of the Web. A search engine takes the user's keywords to retrieve and to rank those pages that contain the keywords. One shortcoming of existing search techniques is that they do not give due consideration to the micro-structures of a Web page. A Web page is often populated with a number of small information units, which we call micro information units (MIU). Each unit focuses on a specific topic and occupies a specific area of the page. During the search, if all the keywords in the user query occur in a single MIU of a page, the top ranking results returned by a search engine are generally relevant and useful. However, if the query words scatter at different MIUs in a page, the pages returned can be quite irrelevant (which causes low precision). The reason for this is that although a page has information on individual MIUs, it may not have information on their intersections. In this paper, we propose a technique to solve this problem. At the off-line pre-processing stage, we segment each page to identify the MIUs in the page, and index the keywords of the page according to the MIUs in which they occur. In searching, our retrieval and ranking algorithm utilizes this additional information to return those most relevant pages. Experimental results show that this method is able to significantly improve the search precision.
Batch data warehouse maintenance in dynamic environments
Authors: Bin Liu, Songting Chen, Elke A. Rundensteiner
Venue: CIKM
Year: 2002

Data warehouse view maintenance is an important issue due to the growing use of warehouse technology for information integration and data analysis. Given the dynamic nature of modern distributed environments, both data updates and schema changes are likely to occur in different data sources. In applications that the real-time refreshment of data warehouse extent under source changes is not critical, the source updates are usually maintained in a batch fashion to reduce the maintenance overhead. However, most prior work can only deal with batch source data updates. In this paper, we provide a solution strategy that is capable of batching both source data updates and schema changes. We propose techniques to first preprocess the initial source updates to summarize delta changes for each source. We then design a view adaptation algorithm to adapt the warehouse view under these delta changes. We have implemented our solutions and incorporated into an existing data warehouse prototype system. The experimental studies demonstrate excellent performance achievable by our batch techniques.
A singer identification technique for content-based classification of MP3 music objects
Authors: Chih-Chin Liu, Chuan-Sung Huang
Venue: CIKM
Year: 2002

As there is a growing amount of MP3 music data available on the Internet today, the problems related to music classification and content-based music retrieval are getting more attention recently. In this paper, we propose an approach to automatically classify MP3 music objects according to their singers. First, the coefficients extracted from the output of the polyphase filters are used to compute the MP3 features for segmentation. Based on these features, an MP3 music object can be decomposed into a sequence of notes (or phonemes). Then for each MP3 phoneme in the training set, its MP3 feature is extracted and used to train an MP3 classifier which can identify the singer of an unknown MP3 music object. Experiments are performed and analyzed to show the effectiveness of the proposed method.
Analysis of pre-computed partition top method for range top-k queries in OLAP data cubes
Authors: Zheng Xuan Loh, Tok Wang Ling, Chuan-Heng Ang, Sin Yeung Lee
Venue: CIKM
Year: 2002

In decision support systems, having knowledge on the top k values is more informative and crucial than the maximum value. Unfortunately, the naive method involves high computational cost and the existing methods for range-max query are inefficient if applied directly. In this paper, we propose a Pre-computed Partition Top method (PPT) to partition the data cube and pre-store a number of top values for improving query performance. The main focus of this study is to find the optimum values for two parameters, i.e., the partition factor (b) and the number of pre-stored values (r), through analytical approach. A cost function based on Poisson distribution is used for the analysis. The analytical results obtained are verified against simulation results. It is shown that the PPT method outperforms other alternative methods significantly when proper b and r are used.
Rule-based data quality
Authors: David Loshin
Venue: CIKM
Year: 2002

In the business intelligence/data warehouse user community, there is a growing confusion as to the difference between data cleansing and data quality. While many data cleansing products can help in applying data edits to name and address data, or help in transforming data during an ETL process, there is usually no persistence in this cleansing. This paper describes how we have implemented a business rules approach to build a data validation engine, called GuardianIQ, that transforms declarative data quality rules into code that objectively measures and reports levels of data quality based on user expectations.
Efficient prediction of web accesses on a proxy server
Authors: Wenwu Lou, Hongjun Lu
Venue: CIKM
Year: 2002

Web access prediction is an active research topic with many applications. Various approaches have been proposed for Web access prediction in the domain of individual Web servers but they have to be tailored to the domain of proxy servers to satisfy its special requirements in prediction efficiency and scalability. In this paper, the design and implementation of proxy-based prediction service (PPS) is presented. For prediction efficiency, PPS applies a new prediction scheme which employs a two-layer navigation model to capture both inter-site and intra-site access patterns, incorporated with a bottom-up prediction mechanism that exploits reference locality in proxy logs. For system scalability, PPS manages the navigation model in disk database and adopts a predictive cache replacement strategy for data shipping between the model database and cache. We show the superiority of our prediction scheme over existing approaches and validate our model management and caching strategies, with a detailed performance study using real-world data.
Pruning long documents for distributed information retrieval
Authors: Jie Lu, James P. Callan
Venue: CIKM
Year: 2002

Query-based sampling is a method of discovering the contents of a text database by submitting queries to a search engine and observing the documents returned. In prior research sampled documents were used to build resource descriptions for automatic database selection, and to build a centralized sample database for query expansion and result merging. An unstated assumption was that the associated storage costs were acceptable.When sampled documents are long, storage costs can be large. This paper investigates methods of pruning long documents to reduce storage costs. The experimental results demonstrate that building resource descriptions and centralized sample databases from the pruned contents of sampled documents can reduce storage costs by 54-93% while causing only minor losses in the accuracy of distributed information retrieval.
A syntactic approach for searching similarities within sentences
Authors: Federica Mandreoli, Riccardo Martoglia, Paolo Tiberio
Venue: CIKM
Year: 2002

Textual data is the main electronic form of knowledge representation. Sentences, meant as logic units of meaningful word sequences, can be considered its backbone. In this paper, we propose a solution based on a purely syntactic approach for searching similarities within sentences, named approximate sub2sequence matching. This process being very time consuming, efficiency in retrieving the most similar parts available in large repositories of textual data is ensured by making use of new filtering techniques. As far as the design of the system is concerned, we chose a solution that allows us to deploy approximate sub2 sequence matching without changing the underlying database.
Knowledge discovery in patent databases
Authors: Konstantinos Markellos, Katerina Perdikuri, Penelope Markellou, Spiros Sirmakessis, George Mayritsakis, Athanasios K. Tsakalidis
Venue: CIKM
Year: 2002

In our days the business, scientific and personal databases are growing in an exponential rate. However, what is truly valuable is the knowledge that can be extracted from the stored data. Knowledge Discovery in patent databases was traditionally based on manual analysis carried out from statistical experts. Nowadays the increasing interest of many actors have led to the development of new tools for discovering and exploiting information related to technological activities and innovation, "hidden" in patent databases. In this paper we present a system that combines efficient and innovative methodologies and tools for the analysis of patent data stored in international databases and the production of scientific and technological indicators.
Mining temporal classes from time series data
Authors: Masahiro Motoyoshi, Takao Miura, Kohei Watanabe
Venue: CIKM
Year: 2002

In this investigation, we discuss how to mine Temporal Class Schemes to model a collection of time series data. From the viewpoint of temporal data mining, this problem can be seen as discretizing time series data or aggregating them. Also this can be considered as screening (or noise filtering). From the viewpoint of temporal databases, the issue is how we represent the data and how we can obtain intensional aspects as temporal schemes. In other words, we discuss scheme discovery for temporal data. Given a collection of temporal objects along with time axis (called log), we examine the data and we introduce a notion of temporal frequent classes to describe them. As the main results of this investigation, we can show that there exists one and only one interval decomposition and the temporal classes related to them. Also we give experimental results that prove the feasibility to time series data.