International Journal of Computational Linguistics & Chinese Language Processing, Volume 21, Number 1, June 2016

International Journal of Computational Linguistics & Chinese Language Processing Aims and Scope International Journal of Computational Linguistics and Chinese Language Processing (IJCLCLP) is an international journal published by the Association for Computational Linguistics and Chinese Language Processing (ACLCLP). This journal was founded in August 1996 and is published four issues per year since 2005. This journal covers all aspects related to computational linguistics and speech/text processing of all natural languages. Possible topics for manuscript submitted to the journal include, but are not limited to: • Computational Linguistics • Natural Language Processing • Machine Translation • Language Generation • Language Learning • Speech Analysis/Synthesis • Speech Recognition/Understanding • Spoken Dialog Systems • Information Retrieval and Extraction • Web Information Extraction/Mining • Corpus Linguistics • Multilingual/Cross-lingual Language Processing Membership & Subscriptions If you are interested in joining ACLCLP, please see appendix for further information. Copyright © The Association for Computational Linguistics and Chinese Language Processing International Journal of Computational Linguistics and Chinese Language Processing is published four issues per volume by the Association for Computational Linguistics and Chinese Language Processing. Responsibility for the contents rests upon the authors and not upon ACLCLP, or its members. Copyright by the Association for Computational Linguistics and Chinese Language Processing. All rights reserved. No part of this journal may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical photocopying, recording or otherwise, without prior permission in writing form from the Editor-in Chief. Cover Calligraphy by Professor Ching-Chun Hsieh, founding president of ACLCLP Text excerpted and compiled from ancient Chinese classics, dating back to 700 B.C. This calligraphy honors the interaction and influence between text and language International Journal of Computational Linguistics and Chinese Language Processing vol. 21, no. 1, June 2016 Contents Papers A Segmentation Matrix Method for Chinese Segmentation Ambiguity Analysis......................................................................... Yanping Chen, Qinghua Zheng, Feng Tian, and Deli Zhen 1 Linguistic Template Extraction for Recognizing Reader-Emotion. Yung-Chun Chang, Chun-Han Chu, Chien Chin Chen, and Wen-Lian Hsu 29 Enriching Cold Start Personalized Language Model Using Social Network Information....................................................................... Yu-Yang Huang, Rui Yan, Tsung-Ting Kuo, and Shou-De Lin 51 Identifying the Names of Complex Search Tasks with Task-Related Entities.…………………………………………….. Ting-Xuan Wang, and Wen-Hsiang Lu 69 The Association for Computational Linguistics and Chinese Language Processing Computational Linguistics and Chinese Language Processing Vol. 21, No. 1, June 2016, pp. 1-28 1  The Association for Computational Linguistics and Chinese Language Processing A Segmentation Matrix Method for Chinese Segmentation Ambiguity Analysis Yanping Chen,, Qinghua Zheng, Feng Tian, and Deli Zheng Abstract Chinese Segmentation Ambiguity (CSA) is a fundamental problem confronted when processing Chinese language, where a sentence can generate more than one segmentation paths. Two techniques are commonly used to identify CSA: Omni-segmentation and Bi-directional Maximum Matching (BiMM). Due to the high computational complexity, Omni-segmentation is difficult to be applied for big data. BiMM is easier to be implemented and has a higher speed. However, recall of BiMM is much lower. In this paper, a Segmentation Matrix (SM) method is …

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