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  • × author_ss:"Tseng, Y.-H."
  • × year_i:[2000 TO 2010}
  1. Tseng, Y.-H.: Automatic thesaurus generation for Chinese documents (2002) 0.00 
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    Abstract
    Tseng constructs a word co-occurrence based thesaurus by means of the automatic analysis of Chinese text. Words are identified by a longest dictionary match supplemented by a key word extraction algorithm that merges back nearby tokens and accepts shorter strings of characters if they occur more often than the longest string. Single character auxiliary words are a major source of error but this can be greatly reduced with the use of a 70-character 2680 word stop list. Extracted terms with their associate document weights are sorted by decreasing frequency and the top of this list is associated using a Dice coefficient modified to account for longer documents on the weights of term pairs. Co-occurrence is not in the document as a whole but in paragraph or sentence size sections in order to reduce computation time. A window of 29 characters or 11 words was found to be sufficient. A thesaurus was produced from 25,230 Chinese news articles and judges asked to review the top 50 terms associated with each of 30 single word query terms. They determined 69% to be relevant.
    Type
    a
  2. Tseng, Y.-H.; Lin, C.-J.; Lin, Y.-I.: Text mining techniques for patent analysis (2007) 0.00 
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    Abstract
    Patent documents contain important research results. However, they are lengthy and rich in technical terminology such that it takes a lot of human efforts for analyses. Automatic tools for assisting patent engineers or decision makers in patent analysis are in great demand. This paper describes a series of text mining techniques that conforms to the analytical process used by patent analysts. These techniques include text segmentation, summary extraction, feature selection, term association, cluster generation, topic identification, and information mapping. The issues of efficiency and effectiveness are considered in the design of these techniques. Some important features of the proposed methodology include a rigorous approach to verify the usefulness of segment extracts as the document surrogates, a corpus- and dictionary-free algorithm for keyphrase extraction, an efficient co-word analysis method that can be applied to large volume of patents, and an automatic procedure to create generic cluster titles for ease of result interpretation. Evaluation of these techniques was conducted. The results confirm that the machine-generated summaries do preserve more important content words than some other sections for classification. To demonstrate the feasibility, the proposed methodology was applied to a real-world patent set for domain analysis and mapping, which shows that our approach is more effective than existing classification systems. The attempt in this paper to automate the whole process not only helps create final patent maps for topic analyses, but also facilitates or improves other patent analysis tasks such as patent classification, organization, knowledge sharing, and prior art searches.
    Type
    a
  3. Tseng, Y.-H.: Automatic cataloguing and searching for retrospective data by use of OCR text (2001) 0.00 
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    Abstract
    This article describes our efforts in supporting information retrieval from OCR degraded text. In particular, we report our approach to an automatic cataloging and searching contest for books in multiple languages. In this contest, 500 books in English, German, French, and Italian published during the 1770s to 1970s are scanned into images and OCRed to digital text. The goal is to use only automatic ways to extract information for sophisticated searching. We adopted the vector space retrieval model, an n-gram indexing method, and a special weighting scheme to tackle this problem. Although the performance by this approach is slightly inferior to the best approach, which is mainly based on regular expression match, one advantage of our approach is that it is less language dependent and less layout sensitive, thus is readily applicable to other languages and document collections. Problems of OCR text retrieval for some Asian languages are also discussed in this article, and solutions are suggested
    Type
    a

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