Journal of Intelligent Information Systems
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The epistemology of conceptual clustering: KBG, an implementation
Journal of Intelligent Information Systems - Tập 1 Số 1 - Trang 57-84 - 1992
Token-Templates and Logic Programs for Intelligent Web Search
Journal of Intelligent Information Systems - Tập 14 - Trang 241-261 - 2000
We present a general framework for the information extraction from web pages based on a special wrapper language, called token-templates. By using token-templates in conjunction with logic programs we are able to reason about web page contents, search and collect facts and derive new facts from various web pages. We give a formal definition for the semantics of logic programs extended by token-tem......
Mining top-k frequent patterns over data streams sliding window
Journal of Intelligent Information Systems - Tập 42 - Trang 111-131 - 2013
Frequent pattern mining in data streams is an important research topic in the data mining community. In previous studies, a minimum support threshold was assumed to be available for mining frequent patterns. However, setting such a threshold is typically difficult. Hence, it is more reasonable to ask users to set a bound on the result size. The present study considers mining top-k frequent pattern......
Hybrid data labeling algorithm for clustering large mixed type data
Journal of Intelligent Information Systems - - 2014
Due to enormous growth in both volume and variety of data, clustering a very large database is a time-consuming process. To speed up clustering process, sampling has been recognized as a very utilitarian approach to reduce the dataset size in which a collection of data points are taken as a sample and then a clustering algorithm is applied to partitioning the data points in that sample into cluste......
Data model and query evaluation in global information systems
Journal of Intelligent Information Systems - Tập 5 - Trang 121-143 - 1995
Global information systems involve a large number of information sources distributed over computer networks. The variety of information sources and disparity of interfaces makes the task of easily locating and efficiently accessing information over the network very cumbersome. We describe an architecture for global information systems that is especially tailored to address the challenges raised in......
Introduction to the special issue on networked information discovery and retrieval
Journal of Intelligent Information Systems - Tập 5 - Trang 79-79 - 1995
Predicting the popularity of topics based on user sentiment in microblogging websites
Journal of Intelligent Information Systems - Tập 51 - Trang 97-114 - 2017
Behavioral economics show us that emotions play an important role in individual behavior and decision-making. Does this also affect collective decision making in a community? Here we investigate whether the community sentiment energy of a topic is related to the spreading popularity of the topic. To compute the community sentiment energy of a topic, we first analyze the sentiment of a user on the ......
A new approach for combining content-based and collaborative filters
Journal of Intelligent Information Systems - Tập 27 - Trang 79-91 - 2006
With the development of e-commerce and the proliferation of easily accessible information, recommender systems have become a popular technique to prune large information spaces so that users are directed toward those items that best meet their needs and preferences. A variety of techniques have been proposed for performing recommendations, including content-based and collaborative techniques. Cont......
Multi-view document clustering via ensemble method
Journal of Intelligent Information Systems - - 2014
Labelset topic model for multi-label document classification
Journal of Intelligent Information Systems - Tập 46 - Trang 83-97 - 2014
It has recently been suggested that assuming independence between labels is not suitable for real-world multi-label classification. To account for label dependencies, this paper proposes a supervised topic modeling algorithm, namely labelset topic model (LsTM). Our algorithm uses two labelset layers to capture label dependencies. LsTM offers two major advantages over existing supervised topic mode......
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