By Jiali Yun, Liping Jing, Jian Yu, Houkuan Huang (auth.), Rossitza Setchi, Ivan Jordanov, Robert J. Howlett, Lakhmi C. Jain (eds.)
th The 14 foreign convention on Knowledge-Based and clever details and Engineering structures used to be held in the course of September 8–10, 2010 in Cardiff, united kingdom. The convention was once prepared via the college of Engineering at Cardiff college, united kingdom and KES foreign. KES2010 supplied a world clinical discussion board for the presentation of the - sults of fine quality examine on a vast diversity of clever platforms subject matters. The c- ference attracted over 360 submissions from forty two international locations and six continents: Argentina, Australia, Belgium, Brazil, Bulgaria, Canada, Chile, China, Croatia, Czech Republic, Denmark, Finland, France, Germany, Greece, Hong Kong ROC, Hungary, India, Iran, eire, Israel, Italy, Japan, Korea, Malaysia, Mexico, The Netherlands, New Zealand, Pakistan, Poland, Romania, Singapore, Slovenia, Spain, Sweden, Syria, Taiwan, - nisia, Turkey, united kingdom, united states and Vietnam. The convention consisted of 6 keynote talks, eleven common tracks and 29 invited s- sions and workshops, at the functions and concept of clever structures and similar components. the celebrated keynote audio system have been Christopher Bishop, united kingdom, Nikola - sabov, New Zealand, Saeid Nahavandi, Australia, Tetsuo Sawaragi, Japan, Yuzuru Tanaka, Japan and Roger Whitaker, united kingdom. Over 240 oral and poster shows supplied very good possibilities for the presentation of fascinating new learn effects and dialogue approximately them, resulting in wisdom move and new release of recent rules. prolonged types of chosen papers have been thought of for e-book within the Int- nationwide magazine of Knowledge-Based and clever Engineering structures, Engine- ing purposes of synthetic Intelligence, magazine of clever production, and Neural Computing and Applications.
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Extra info for Knowledge-Based and Intelligent Information and Engineering Systems: 14th International Conference, KES 2010, Cardiff, UK, September 8-10, 2010, Proceedings, Part II
Shankar, and V. Pudi the approach we propose, we take the Wikipedia categories of all the documents of a cluster and ﬁnd out the top k frequently occurring categories and assign them as the labels to the cluster. We ﬁnd this method more interesting because categories in Wikipedia represent a more general sense of the documents in the cluster (like the parent nodes in a hierarchy). 6 Experimental Evaluation We performed extensive experiments on 5 standard datasets of varying characteristics like number of documents, number of classes, etc.
They are also topic-independent. Therefore, function words are good indicators of the author’s style. It is diﬃcult to predict whether these words will give equally good results for diﬀerent languages. Moreover, despite the abundance of research in this ﬁeld, due to various languages, types and sizes of the texts, it is currently impossible to conclude if these features are generally eﬀective . 24 T. Reicher et al. In addition to function words, in this work we also consider frequencies of auxiliary verbs and pronouns.
Gabrilovich and Markovitch [11,12] propose a method to improve text classiﬁcation performance by enriching document representation with Wikipedia concepts. Further, [13,14] present a framework for using Wikipedia concepts and categories in document clustering. Out of the existing knowledge repositories, we chose wikipedia because it captures a wide range of domains, is frequently updated, is ontologically well structured, and is less noisy. [11,12] 4 Our Approach : Overview In our approach, we ﬁrst apply any simple frequent itemset mining algorithm like Apriori on all the documents to mine the frequent itemsets.