Results 1 - 10 of 329

Meta-Learning in Distributed Data Mining Systems: Issues and Approaches

by Andreas L. Prodromidis, Philip K. Chan, Salvatore J. Stolfo - Advances of Distributed Data Mining , 2000
"... Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach to this objective is to apply various machine learning algorithms to compute descriptive models of the available data. Here, we explore one of the main challeng ..."
Abstract - Cited by 103 (0 self) - Add to MetaCart
Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach to this objective is to apply various machine learning algorithms to compute descriptive models of the available data. Here, we explore one of the main

Exploration of the Power of Attribute-Oriented Induction in Data Mining

by Jiawei Han, Yongjian Fu , 1996
"... Attribute-oriented induction is a set-oriented database mining method which generalizes the task-relevant subset of data attribute-by-attribute, compresses it into a generalized relation, and extracts from it the general features of data. In this chapter, the power of attribute-oriented induction is ..."
Abstract - Cited by 69 (14 self) - Add to MetaCart
Attribute-oriented induction is a set-oriented database mining method which generalizes the task-relevant subset of data attribute-by-attribute, compresses it into a generalized relation, and extracts from it the general features of data. In this chapter, the power of attribute-oriented induction

Architectural Design Recovery using Data Mining Techniques

by Kamran Sartipi, Kostas Kontogiannis, Farhad Mavaddat , 2000
"... This paper presents a technique for recovering the high level design of legacy software systems according to user defined architectural plans. Architectural plans are represented using a description language and specify system components and their interfaces. Such descriptions are viewed as queries ..."
Abstract - Cited by 24 (3 self) - Add to MetaCart
that are applied on a large data base which stores information extracted from the source code of the subject legacy system. Data mining techniques and a modified branch and bound search algorithm are used to control the matching process, by which the query is satisfied and query variables are instantiated

Visualizing Sequential Patterns for Text Mining

by Pak Chung Wong, Wendy Cowley, Harlan Foote, Elizabeth Jurrus, Jim Thomas - Proc. IEEE Information Visualization, 2000 , 2000
"... A sequential pattern in data mining is a finite series of elements such as A B C D where A, B, C, and D are elements of the same domain. The mining of sequential patterns is designed to find patterns of discrete events that frequently happen in the same arrangement along a timeline. Like associat ..."
Abstract - Cited by 25 (0 self) - Add to MetaCart
association and clustering, the mining of sequential patterns is among the most popular knowledge discovery techniques that apply statistical measures to extract useful information from large datasets. As our computers become more powerful, we are able to mine bigger datasets and obtain hundreds of thousands

Feature Level Opinion Mining of Educational Student Feedback Data using Sequential Pattern Mining and Association Rule Mining

by Ayesha Rashid, Naveed Anwer Butt, Imran Ashraf
"... This research paper combines the data mining with natural language processing to extract the nuggets of knowledge from massive volume of student feedback dataset on faculty performance. The main objective is to compare two renowned association rule mining and sequential pattern mining algorithms nam ..."
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This research paper combines the data mining with natural language processing to extract the nuggets of knowledge from massive volume of student feedback dataset on faculty performance. The main objective is to compare two renowned association rule mining and sequential pattern mining algorithms

Pattern-Miner: Integrated Management and Mining over Data Mining Models

by Evangelos E Kotsifakos, Irene Ntoutsi, Yannis Vrahoritis, Yannis Theodoridis
"... This demo presents Pattern-Miner, an integrated environment for pattern management and mining that deals with the whole lifecycle of patterns, from their generation (using data mining techniques) to their storage and querying, putting also emphasis on the comparison between patterns and meta-mining ..."
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operations over the extracted patterns. Pattern comparison (comparing results of the data mining process) and meta-mining are high level pattern operations that can be applied in a variety of applications, from database change management to image comparison and retrieval.

Mining Patterns from Case Base Analysis

by Tao Li, Shenghuo Zhu, Mitsunori Ogihara , 2001
"... In this paper, we present our work on combining domain knowledge and data mining techniques for improve the service and realize cost reduction for a product company. We first extract domain knowledge from the database of call records and then incorporate the domain knowledge into the process of find ..."
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In this paper, we present our work on combining domain knowledge and data mining techniques for improve the service and realize cost reduction for a product company. We first extract domain knowledge from the database of call records and then incorporate the domain knowledge into the process

Data Mining for Typhoon Image Collection

by Asanobu Kitamoto - In 2nd Int. Workshop on Multimedia Data Mining , 2001
"... Abstract. Our research aims at discovering useful knowledge from the large collection of satellite images of typhoons using data mining approaches. We first introduce the creation of the typhoon image collection that consists of around 34,000 typhoon images for the northern and southern hemisphere, ..."
Abstract - Cited by 12 (2 self) - Add to MetaCart
, providing the medium-sized, richly-variational and quality-controlled data collection suitable for spatio-temporal data mining research. Next we apply several data mining approaches for this image collection. We start with spatial data mining, where principal component analysis is used for extracting basic

A.: Mining graph evolution rules

by Michele Berlingerio, Francesco Bonchi, Björn Bringmann, Aristides Gionis - In: ECML/PKDD , 2009
"... Abstract. In this paper we introduce graph-evolution rules, a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level. Given a sequence of snapshots of an evolving graph, we aim at discovering rules describing the local changes occurring in it. ..."
Abstract - Cited by 37 (4 self) - Add to MetaCart
. Adopting a definition of support based on minimum image we study the problem of extracting patterns whose frequency is larger than a minimum support threshold. Then, similar to the classical association rules framework, we derive graph-evolution rules from frequent patterns that satisfy a given minimum

Page-Level Data Extraction from Template Web Pages

by Ms. Deepali, S. Patil, Prof S. K. Shinde
"... Abstract- A huge amount of information on the World Wide Web has a structured HTML form as they are generated dynamically from databases and have the same template. This paper proposes a page-level web data extraction system that extracts schema and templates from these template-based web pages auto ..."
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automatically. The proposed system uses visual clues for comparing web pages for fixed/variant template detection. From fixed template pages, we construct pattern tree which is used to detect schema & extract data. It detects schema by applying tree merging, tree alignment and mining techniques
Results 1 - 10 of 329