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User Preference Modeling from Positive Contents for Personalized Recommendation
With the spread of the Web, users can obtain a wide variety of information, and also can access novel content in real time. In this environment,...
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Fast NML Computation for Naive Bayes Models
The Minimum Description Length (MDL) is an informationtheoretic principle that can be used for model selection and other statistical inference tasks....
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Towards Future Technology Projection: A Method for Extracting Capability Phrases from Documents
This paper deals with novel approaches for discovering phrases expressing technical capabilities in technical literature (such as patents), intended...
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Detecting Concept Drift Using Statistical Testing
Detecting concept drift is important for dealing with real-world online learning problems. To detect concept drift in a small number of examples,...
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Literature-Based Discovery by an Enhanced Information Retrieval Model
The massive, ever-growing literature in life science makes it increasingly difficult for individuals to grasp all the information relevant to their...
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Active Contours as Knowledge Discovery Methods
In the paper we show that active contour methods can be interpreted as knowledge discovery methods. Application area is not restricted only to image...
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Iterative Reordering of Rules for Building Ensembles Without Relearning
We study a new method for improving the classification accuracy of a model composed of classification association rules (CAR). The method consists in...
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Discovery Science 10th International Conference, DS 2007 Sendai, Japan, October 1-4, 2007. Proceedings
This volume contains the papers presented at DS-2007:The Tenth International Conference on Discovery Science held in Sendai, Japan, October 1–4,...
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A Theoretical Study on Variable Ordering of Zero-Suppressed BDDs for Representing Frequent Itemsets
Recently, an efficient method of database analysis using Zero-suppressed Binary Decision Diagrams (ZBDDs) has been proposed. BDDs are a graph-based...
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Challenge for Info-plosion
Information created by people has increased rapidly since the year 2000, and now we are in a time which we could call the “information-explosion...
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Machine Learning in Ecosystem Informatics
The emerging field of Ecosystem Informatics applies methods from computer science and mathematics to address fundamental and applied problems in the...
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Model Selection and Estimation Via Subjective User Preferences
Subjective opinions of domain experts are often encountered in data analysis projects. Often, it is difficult to express the experts’ opinions in...
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An Intentional Kernel Function for RNA Classification
This paper presents a kernel function class K RNA which is based on the concept of the...
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On Approximating Minimum Infrequent and Maximum Frequent Sets
The maximum cardinality of a frequent set as well as the minimum cardinality of an infrequent set are important characteristic numbers in frequent...
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A Hilbert Space Embedding for Distributions
While kernel methods are the basis of many popular techniques in supervised learning, they are less commonly used in testing, estimation, and...
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Efficient Incremental Mining of Top-K Frequent Closed Itemsets
In this work we study the mining of top-K frequent closed itemsets, a recently proposed variant of the classical problem of mining frequent closed...
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Unsupervised Spam Detection Based on String Alienness Measures
We propose an unsupervised method for detecting spam documents from a given set of documents, based on equivalence relations on strings. We give...
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Reducing Trials by Thinning-Out in Skill Discovery
In this paper, we propose a new concept, thinning-out, for reducing the number of trials in skill discovery. Thinning-out means to skip over such...
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A Consequence Finding Approach for Full Clausal Abduction
Abductive inference has long been associated with the logic of scientific discovery and automated abduction is now being used in real scientific...
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An Efficient Polynomial Delay Algorithm for Pseudo Frequent Itemset Mining
Mining frequently appearing patterns in a database is a basic problem in informatics, especially in data mining. Particularly, when the input...