-A series of experiments is being conducted on the Farsi language in the domain of laws in the university of Tehran. One of the goals of these experiments is to establish the performance of different weighting schemes and retrieval models. For the lack of a Farsi stemmer and some characterisitics of the language, it was decided to experiment with N-grams. With un-stemmed words and 2-grams, 3-gr...

1 Text mining draw more and more attention recently, it has been applied on different domains including web mining, opinion mining, and sentiment analysis. Text pre-processing is an important stage in text mining. The major obstacle in text mining is the very high dimensionality and the large size of text data. Natural language processing and morphological tools can be employed to reduce dimens...

Simulation schemes for probabilistic infer­ ence in Bayesian belief networks offer many advantages over exact algorithms; for ex­ ample, these schemes have a linear and thus predictable runtime while exact algo­ rithms have exponential runtime. Exper­ iments have shown that likelihood weight­ ing is one of the most promising simulation schemes. In this paper, we present a new simulation scheme ...

Information retrieval from textual data focuses on the construction of vocabularies that contain weighted term tuples. Such vocabularies can then be exploited by various text analysis algorithms to extract new knowledge, e.g., top-k keywords, top-k documents, etc. Topk keywords are casually used for various purposes, are often computed on-the-fly, and thus must be efficiently computed. To compa...

The rigorous analysis of crystallographic models, refined through the use of least-squares minimization, is founded on the expectation that the data provided have a normal distribution of residuals. Processed single-crystal diffraction data rarely exhibit this feature without a weighting scheme being applied. These schemes are designed to reflect the precision and accuracy of the measurement of...

Voting systems typically treat all voters equally. We argue that perhaps they should not: Voters who have supported good choices in the past should be given higher weight than voters who have supported bad ones. To develop a formal framework for desirable weighting schemes, we draw on no-regret learning. Specifically, given a voting rule, we wish to design a weighting scheme such that applying ...

The traditional data-driven prognostic approach is to construct multiple candidate algorithms using a training data set, evaluate their respective performance using a testing data set, and select the one with the best performance while discarding all the others. This approach has three shortcomings: (i) the selected standalone algorithm may not be robust, i.e., it may be less accurate when the ...