916 Result(s)
within
English
Artificial Intelligence
Data Mining and Knowledge Discovery
Information Systems Applications (incl. Internet)
Jian** **
Conference Paper
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Chapter and Conference Paper
Planning with Domain Rules Based on State-Independent Activation Sets
In AI planning community, planning domains with derived predicates are very challenging to many planning system. Derived predicate is a new application of domain rules and domain knowledge acquisition. In this...
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Chapter and Conference Paper
Extracting Minimum Unsatisfiable Cores with a Greedy Genetic Algorithm
Explaining the causes of infeasibility of Boolean formulas has practical applications in various fields. We are generally interested in a minimum explanation of infeasibility that excludes irrelevant informati...
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Chapter and Conference Paper
Hybrid O( \(n \sqrt{n}\) ) Clustering for Sequential Web Usage Mining
We propose a natural neighbor inspired O( \(n \sqrt{n}\) ) hybrid clustering algorithm that combines medoid-based partiti...
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Chapter and Conference Paper
Training Classifiers for Unbalanced Distribution and Cost-Sensitive Domains with ROC Analysis
ROC (Receiver Operating Characteristic) has been used as a tool for the analysis and evaluation of two-class classifiers, even the training data embraces unbalanced class distribution and cost-sensitiveness. H...
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Chapter and Conference Paper
Clustering Massive Text Data Streams by Semantic Smoothing Model
Clustering text data streams is an important issue in data mining community and has a number of applications such as news group filtering, text crawling, document organization and topic detection and tracing e...
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Chapter and Conference Paper
Pattern Recognition in Stock Data Based on a New Segmentation Algorithm
In trying to find the features and patterns within the stock time series, time series segmentation is often required as one of the fundamental components in stock data mining. In this paper, a new stock time s...
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Chapter and Conference Paper
An Improved AdaBoost Algorithm Based on Adaptive Weight Adjusting
The base classifier, which is trained by AdaBoost ensemble learning algorithm, has a constant weight for all test instances. From the view of iterative process of AdaBoost, every base classifier has good class...
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Chapter and Conference Paper
Reduction Based Symbolic Value Partition
Theory of Rough Sets provides good foundations for the attribute reduction processes in data mining. For numeric attributes, it is enriched with appropriately designed discretization methods. However, not much...
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Chapter and Conference Paper
Unsupervised Outlier Detection in Sensor Networks Using Aggregation Tree
In the applications of sensor networks, outlier detection has attracted more and more attention. The identification of outliers can be used to filter false data, find faulty nodes and discover interesting even...
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Chapter and Conference Paper
Clustering-Based K-Anonymisation Algorithms
K-anonymisation is an approach to protecting private information contained within a dataset. Many k-anonymisation methods have been proposed recently and one class of such methods are clustering-based. These m...
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Chapter and Conference Paper
A Novel Text Classification Approach Based on Enhanced Association Rule
The current research on association rule based text classification neglected several key problems. First, weights of elements in profile vectors may have much impact on generating classification rules. Second,...
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Chapter and Conference Paper
A Subjective and Objective Integrated Method for MAGDM Problems with Multiple Types of Exact Preference Formats
Group decision making with preference information on alternatives has become a very active research field over the last decade. Especially, the investigation on the group decision making problems based on diff...
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Chapter and Conference Paper
Exploiting Uncertain Data in Support Vector Classification
A new approach of input uncertainty classification is proposed in this paper. This approach develops a new technique which extends the support vector classification (SVC) by incorporating input uncertainties. ...
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Chapter and Conference Paper
A Fast Reading Spatial Knowledge System by Ultrasonic Sound Beams
PC users can retrieve lots of common information by Internet search engines. A text-to-speech (TTS) system allows citizens to easily access the public report from the city etc. However it takes a long time for...
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Chapter and Conference Paper
Distributed Knowledge Management Based on Ontological Engineering and Multi-Agent System Towards Semantic Interoperation
Currently, the available architectures for knowledge management are mainly centralized and focus on basic string processing in essence. They tend to ignore that knowledge is distributed and full of semantics i...
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Chapter and Conference Paper
A Distributed Genetic Algorithm for Optimizing the Quality of Grid Workflow
The advancement of Grid and Web service technologies greatly facilitates the aggregation of distributed applications. As the grid workflow generally involves long lasting execution tasks, the quality optimizat...
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Chapter and Conference Paper
CACS: A Novel Classification Algorithm Based on Concept Similarity
This paper proposes a novel algorithm of classification based on the similarities among data attributes. This method assumes data attributes of dataset as basic vectors of m dimensions, and each tuple of datas...
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Chapter and Conference Paper
Exploring Content and Linkage Structures for Searching Relevant Web Pages
This work addresses the problem of Web searching for pages relevant to a query URL. Based on an approach that uses a deep linkage analysis among vicinity pages, we investigate the Web page content structures a...
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Chapter and Conference Paper
Finding Unsatisfiable Subformulas with Stochastic Method
Explaining the causes of infeasibility of Boolean formulas has many practical applications in various fields. A small unsatisfiable subformula provides a succinct explanation of infeasibility and is valuable f...
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Chapter and Conference Paper
Independent Factor Reinforcement Learning for Portfolio Management
In this paper we propose to do portfolio management using reinforcement learning (RL) and independent factor model. Factors in independent factor model are mutually independent and exhibit better predictabilit...
