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Purpose -The paper's aim is to propose a core journal decision method, called the local impact factor (LIF), which can evaluate the requirements of the local user community by combining both the access rate and the weighted impact factor, and by tracking citation information on the local users' articles. Design/methodology/approach -Many institutions with a limited budget can subscribe only to the most valuable journals for their users. The importance of a journal to a local community can be calculated in many ways. This paper takes both global and local access frequency and journal citations into consideration. The method of weighted web page link analysis is adopted.Findings -This paper finds that the weighted page rank may be used efficiently in the core journal decisions. Experimental results demonstrate that the proposed LIF can effectively suggest journals to local users better than existing methods (i.e. impact factor or the local journal rank). Research limitations/implications -This research requires the determination of the thesis scores, which needs authorisation from the authors. If the scores are not available, the scores may be subjectively assigned or retrieved from the other resources. Practical implications -A case study in National Cheng Kung University was conducted to show that the LIF can be used to help library managers evaluate the real demands of local community users. Originality/value -Rather than existing research, this paper focuses on the utilisation and requirements of local community users and also finds the contributions of citation information to be significant and critical.

Purpose -The purpose of this paper is to develop a novel feature selection approach for automatic text classification of large digital documentse-books of online library system. The main idea mainly aims on automatically identifying the discourse features in order to improving the feature selection process rather than focussing on the size of the corpus. Design/methodology/approach -The proposed framework intends to automatically identify the discourse segments within e-books and capture proper discourse subtopics that are cohesively expressed in discourse segments and treating these subtopics as informative and prominent features. The selected set of features is then used to train and perform the e-book classification task based on the support vector machine technique. Findings -The evaluation of the proposed framework shows that identifying discourse segments and capturing subtopic features leads to better performance, in comparison with two conventional feature selection techniques: TFIDF and mutual information. It also demonstrates that discourse features play important roles among textual features, especially for large documents such as e-books. Research limitations/implications -Automatically extracted subtopic features cannot be directly entered into FS process but requires control of the threshold. Practical implications -The proposed technique has demonstrated the promised application of using discourse analysis to enhance the classification of large digital documentse-books as against to conventional techniques. Originality/value -A new FS technique is proposed which can inspect the narrative structure of large documents and it is new to the text classification domain. The other contribution is that it inspires the consideration of discourse information in future text analysis, by providing more evidences through evaluation of the results. The proposed system can be integrated into other library management systems.2 PROG 49,1 digitalized format, which provides several benefits to readers, including shortened publication cycles, faster distribution channels that permit the wider propagation of timely information, and friendly visualization to display deliberate content of articles. As regarding the essence of content, e-book is different from other type of textual materials because it usually contains lengthy content which easily leads to higher feature dimension in the perspective of term-level analysis. As such, the book may consist of a variety of themes in the text stream, which are distributed and shifted among sentences or paragraphs in turns of the hidden subtopic to stretch the expression of the main topic (Hearst, 1997;Ridel and Bieman, 2012). Such phenomena mostly addressed in discourse analysis raises interesting issues to text processing problems for which an innovative strategy is needed as exploring the high-level linguistic attributes from e-book.The properties sustaining the lexical coherence of topic imply the flow of discourse information, which is valuable to be further investigated an...