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Traditional sequential patterns do not take into account additional contextual information since patterns extracted from data are usually general. By considering the fact that a pattern is associated with one specific context the decision expert can then adapt his strategy considering the type of customers. In this paper we propose to mine more precise patterns of the form "young users buy products...
We present Bautext, a new minimally supervised approach for automatically extracting ratable aspects from customer reviews and classifying them to some previously defined categories. Bautext requires a small amount of seed words as supervised data and uses a bootstrapping mechanism o progressively collect new member for each category. Learning new category members and the category-specific terms for...
Patterns represent an important tool for communicating, documenting and looking up best practices for both novice and expert system developers and designers. Although there are a number of different patterns and pattern languages available, it is still unclear how to validate patterns in a structured way. Within this paper, we aim to fill this gap by introducing a Quality Criteria Framework developed...
Since whether or not a word is a name is determined mostly by the context of the word, the context pattern induction plays an important role in name entity recognition (NER). We present a NER method based on the context pattern induction. It induces high-precision context patterns in an unsupervised way starting with some entity seeds. Then it uses directly the matched context patterns, instead of...
Contribution: This research contributes a new understanding of classification of learners in a CSET classroom within a conceptual framework. We compared the grades for students in each classification for a few large classrooms. The results were sufficiently interesting to justify further empirical studies on the subject. Description: A particular set of classification of learners, drawn from Malcolm...
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