Search (9 results, page 1 of 1)

  • × author_ss:"Yang, C.C."
  1. Chau, M.; Lu, Y.; Fang, X.; Yang, C.C.: Characteristics of character usage in Chinese Web searching (2009) 0.03
    0.025801437 = product of:
      0.09030502 = sum of:
        0.025943318 = weight(_text_:management in 2456) [ClassicSimilarity], result of:
          0.025943318 = score(doc=2456,freq=2.0), product of:
            0.13932906 = queryWeight, product of:
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.041336425 = queryNorm
            0.18620178 = fieldWeight in 2456, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2456)
        0.06436171 = sum of:
          0.03635913 = weight(_text_:studies in 2456) [ClassicSimilarity], result of:
            0.03635913 = score(doc=2456,freq=2.0), product of:
              0.16494368 = queryWeight, product of:
                3.9902744 = idf(docFreq=2222, maxDocs=44218)
                0.041336425 = queryNorm
              0.22043361 = fieldWeight in 2456, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.9902744 = idf(docFreq=2222, maxDocs=44218)
                0.0390625 = fieldNorm(doc=2456)
          0.028002575 = weight(_text_:22 in 2456) [ClassicSimilarity], result of:
            0.028002575 = score(doc=2456,freq=2.0), product of:
              0.14475311 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.041336425 = queryNorm
              0.19345059 = fieldWeight in 2456, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.0390625 = fieldNorm(doc=2456)
      0.2857143 = coord(2/7)
    
    Abstract
    The use of non-English Web search engines has been prevalent. Given the popularity of Chinese Web searching and the unique characteristics of Chinese language, it is imperative to conduct studies with focuses on the analysis of Chinese Web search queries. In this paper, we report our research on the character usage of Chinese search logs from a Web search engine in Hong Kong. By examining the distribution of search query terms, we found that users tended to use more diversified terms and that the usage of characters in search queries was quite different from the character usage of general online information in Chinese. After studying the Zipf distribution of n-grams with different values of n, we found that the curve of unigram is the most curved one of all while the bigram curve follows the Zipf distribution best, and that the curves of n-grams with larger n (n = 3-6) had similar structures with ?-values in the range of 0.66-0.86. The distribution of combined n-grams was also studied. All the analyses are performed on the data both before and after the removal of function terms and incomplete terms and similar findings are revealed. We believe the findings from this study have provided some insights into further research in non-English Web searching and will assist in the design of more effective Chinese Web search engines.
    Date
    22.11.2008 17:57:22
    Source
    Information processing and management. 45(2009) no.1, S.115-130
  2. Yang, C.C.; Lam, W.: Introduction to the special topic section on multilingual information systems (2006) 0.02
    0.020539764 = product of:
      0.14377834 = sum of:
        0.14377834 = weight(_text_:europe in 5043) [ClassicSimilarity], result of:
          0.14377834 = score(doc=5043,freq=4.0), product of:
            0.25178367 = queryWeight, product of:
              6.091085 = idf(docFreq=271, maxDocs=44218)
              0.041336425 = queryNorm
            0.5710392 = fieldWeight in 5043, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              6.091085 = idf(docFreq=271, maxDocs=44218)
              0.046875 = fieldNorm(doc=5043)
      0.14285715 = coord(1/7)
    
    Abstract
    The information available in languages other than English on the World Wide Web and global information systems is increasing significantly. According to some recent reports. the growth of non-English speaking Internet users is significantly higher than the growth of English-speaking Internet users. Asia and Europe have become the two most-populated regions of Internet users. However, there are many different languages in the many different countries of Asia and Europe. And there are many countries in the world using more than one language as their official languages. For example, Chinese and English are official languages in Hong Kong SAR; English and French are official languages in Canada. In the global economy, information systems are no longer utilized by users in a single geographical region but all over the world. Information can be generated, stored, processed, and accessed in several different languages. All of this reveals the importance of research in multilingual information systems.
  3. Yang, C.C.; Lin, J.; Wei, C.-P.: Retaining knowledge for document management : category-tree integration by exploiting category relationships and hierarchical structures (2010) 0.01
    0.0052413424 = product of:
      0.036689393 = sum of:
        0.036689393 = weight(_text_:management in 3581) [ClassicSimilarity], result of:
          0.036689393 = score(doc=3581,freq=4.0), product of:
            0.13932906 = queryWeight, product of:
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.041336425 = queryNorm
            0.2633291 = fieldWeight in 3581, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3581)
      0.14285715 = coord(1/7)
    
    Abstract
    The category-tree document-classification structure is widely used by enterprises and information providers to organize, archive, and access documents for effective knowledge management. However, category trees from various sources use different hierarchical structures, which usually make mappings between categories in different category trees difficult. In this work, we propose a category-tree integration technique. We develop a method to learn the relationships between any two categories and develop operations such as mapping, splitting, and insertion for this integration. According to the parent-child relationship of the integrating categories, the developed decision rules use integration operations to integrate categories from the source category tree with those from the master category tree. A unified category tree can accumulate knowledge from multiple resources without forfeiting the knowledge in individual category trees. Experiments have been conducted to measure the performance of the integration operations and the accuracy of the integrated category trees. The proposed category-tree integration technique achieves greater than 80% integration accuracy, and the insert operation is the most frequently utilized, followed by map and split. The insert operation achieves 77% of F1 while the map and split operations achieves 86% and 29% of F1, respectively.
  4. Chua, A.Y.K.; Yang, C.C.: ¬The shift towards multi-disciplinarity in information science (2008) 0.00
    0.004447426 = product of:
      0.031131983 = sum of:
        0.031131983 = weight(_text_:management in 2389) [ClassicSimilarity], result of:
          0.031131983 = score(doc=2389,freq=2.0), product of:
            0.13932906 = queryWeight, product of:
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.041336425 = queryNorm
            0.22344214 = fieldWeight in 2389, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.046875 = fieldNorm(doc=2389)
      0.14285715 = coord(1/7)
    
    Abstract
    This article analyzes the collaboration trends, authorship and keywords of all research articles published in the Journal of American Society for Information Science and Technology (JASIST). Comparing the articles between two 10-year periods, namely, 1988-1997 and 1998-2007, the three-fold objectives are to analyze the shifts in (a) authors' collaboration trends (b) top authors, their affiliations as well as the pattern of coauthorship among them, and (c) top keywords and the subdisciplines from which they emerge. The findings reveal a distinct tendency towards collaboration among authors, with external collaborations becoming more prevalent. Top authors have grown in diversity from those being affiliated predominantly with library/information-related departments to include those from information systems management, information technology, businesss, and the humanities. Amid heterogeneous clusters of collaboration among top authors, strongly connected cross-disciplinary coauthor pairs have become more prevalent. Correspondingly, the distribution of top keywords' occurrences that leans heavily on core information science has shifted towards other subdisciplines such as information technology and sociobehavioral science.
  5. Li, K.W.; Yang, C.C.: Automatic crosslingual thesaurus generated from the Hong Kong SAR Police Department Web Corpus for Crime Analysis (2005) 0.00
    0.0029649509 = product of:
      0.020754656 = sum of:
        0.020754656 = weight(_text_:management in 3391) [ClassicSimilarity], result of:
          0.020754656 = score(doc=3391,freq=2.0), product of:
            0.13932906 = queryWeight, product of:
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.041336425 = queryNorm
            0.14896142 = fieldWeight in 3391, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.03125 = fieldNorm(doc=3391)
      0.14285715 = coord(1/7)
    
    Abstract
    For the sake of national security, very large volumes of data and information are generated and gathered daily. Much of this data and information is written in different languages, stored in different locations, and may be seemingly unconnected. Crosslingual semantic interoperability is a major challenge to generate an overview of this disparate data and information so that it can be analyzed, shared, searched, and summarized. The recent terrorist attacks and the tragic events of September 11, 2001 have prompted increased attention an national security and criminal analysis. Many Asian countries and cities, such as Japan, Taiwan, and Singapore, have been advised that they may become the next targets of terrorist attacks. Semantic interoperability has been a focus in digital library research. Traditional information retrieval (IR) approaches normally require a document to share some common keywords with the query. Generating the associations for the related terms between the two term spaces of users and documents is an important issue. The problem can be viewed as the creation of a thesaurus. Apart from this, terrorists and criminals may communicate through letters, e-mails, and faxes in languages other than English. The translation ambiguity significantly exacerbates the retrieval problem. The problem is expanded to crosslingual semantic interoperability. In this paper, we focus an the English/Chinese crosslingual semantic interoperability problem. However, the developed techniques are not limited to English and Chinese languages but can be applied to many other languages. English and Chinese are popular languages in the Asian region. Much information about national security or crime is communicated in these languages. An efficient automatically generated thesaurus between these languages is important to crosslingual information retrieval between English and Chinese languages. To facilitate crosslingual information retrieval, a corpus-based approach uses the term co-occurrence statistics in parallel or comparable corpora to construct a statistical translation model to cross the language boundary. In this paper, the text based approach to align English/Chinese Hong Kong Police press release documents from the Web is first presented. We also introduce an algorithmic approach to generate a robust knowledge base based an statistical correlation analysis of the semantics (knowledge) embedded in the bilingual press release corpus. The research output consisted of a thesaurus-like, semantic network knowledge base, which can aid in semanticsbased crosslingual information management and retrieval.
  6. Yang, C.C.; Li, K.W.: ¬A heuristic method based on a statistical approach for chinese text segmentation (2005) 0.00
    0.002597081 = product of:
      0.018179566 = sum of:
        0.018179566 = product of:
          0.03635913 = sum of:
            0.03635913 = weight(_text_:studies in 4580) [ClassicSimilarity], result of:
              0.03635913 = score(doc=4580,freq=2.0), product of:
                0.16494368 = queryWeight, product of:
                  3.9902744 = idf(docFreq=2222, maxDocs=44218)
                  0.041336425 = queryNorm
                0.22043361 = fieldWeight in 4580, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.9902744 = idf(docFreq=2222, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4580)
          0.5 = coord(1/2)
      0.14285715 = coord(1/7)
    
    Abstract
    The authors propose a heuristic method for Chinese automatic text segmentation based an a statistical approach. This method is developed based an statistical information about the association among adjacent characters in Chinese text. Mutual information of bi-grams and significant estimation of tri-grams are utilized. A heuristic method with six rules is then proposed to determine the segmentation points in a Chinese sentence. No dictionary is required in this method. Chinese text segmentation is important in Chinese text indexing and thus greatly affects the performance of Chinese information retrieval. Due to the lack of delimiters of words in Chinese text, Chinese text segmentation is more difficult than English text segmentation. Besides, segmentation ambiguities and occurrences of out-of-vocabulary words (i.e., unknown words) are the major challenges in Chinese segmentation. Many research studies dealing with the problem of word segmentation have focused an the resolution of segmentation ambiguities. The problem of unknown word identification has not drawn much attention. The experimental result Shows that the proposed heuristic method is promising to segment the unknown words as weIl as the known words. The authors further investigated the distribution of the errors of commission and the errors of omission caused by the proposed heuristic method and benchmarked the proposed heuristic method with a previous proposed technique, boundary detection. It is found that the heuristic method outperformed the boundary detection method.
  7. Chuang, K.Y.; Yang, C.C.: Informational support exchanges using different computer-mediated communication formats in a social media alcoholism community (2014) 0.00
    0.002597081 = product of:
      0.018179566 = sum of:
        0.018179566 = product of:
          0.03635913 = sum of:
            0.03635913 = weight(_text_:studies in 1179) [ClassicSimilarity], result of:
              0.03635913 = score(doc=1179,freq=2.0), product of:
                0.16494368 = queryWeight, product of:
                  3.9902744 = idf(docFreq=2222, maxDocs=44218)
                  0.041336425 = queryNorm
                0.22043361 = fieldWeight in 1179, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.9902744 = idf(docFreq=2222, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1179)
          0.5 = coord(1/2)
      0.14285715 = coord(1/7)
    
    Abstract
    E-patients seeking information online often seek specific advice related to coping with their health condition(s) among social networking sites. They may be looking for social connectivity with compassionate strangers who may have experienced similar situations to share opinions and experiences rather than for authoritative medical information. Previous studies document distinct technological features and different levels of social support interaction patterns. It is expected that the design of the social media functions will have an impact on the user behavior of social support exchange. In this part of a multipart study, we investigate the social support types, in particular information support types, across multiple computer-mediated communication formats (forum, journal, and notes) within an alcoholism community using descriptive content analysis on 3 months of data from a MedHelp online peer support community. We present the results of identified informational support types including advice, referral, fact, personal experiences, and opinions, either offered or requested. Fact type was exchanged most often among the messages; however, there were some different patterns between notes and journal posts. Notes were used for maintaining relationships rather than as a main source for seeking information. Notes were similar to comments made to journal posts, which may indicate the friendship between journal readers and the author. These findings suggest that users may have initially joined the MedHelp Alcoholism Community for information-seeking purposes but continue participation even after they have completed with information gathering because of the relationships they formed with community members through social media features.
  8. Yang, C.C.; Liu, N.: Web site topic-hierarchy generation based on link structure (2009) 0.00
    0.002000184 = product of:
      0.0140012875 = sum of:
        0.0140012875 = product of:
          0.028002575 = sum of:
            0.028002575 = weight(_text_:22 in 2738) [ClassicSimilarity], result of:
              0.028002575 = score(doc=2738,freq=2.0), product of:
                0.14475311 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.041336425 = queryNorm
                0.19345059 = fieldWeight in 2738, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2738)
          0.5 = coord(1/2)
      0.14285715 = coord(1/7)
    
    Date
    22. 3.2009 12:51:47
  9. Yang, C.C.; Luk, J.: Automatic generation of English/Chinese thesaurus based on a parallel corpus in laws (2003) 0.00
    0.0014001287 = product of:
      0.009800901 = sum of:
        0.009800901 = product of:
          0.019601801 = sum of:
            0.019601801 = weight(_text_:22 in 1616) [ClassicSimilarity], result of:
              0.019601801 = score(doc=1616,freq=2.0), product of:
                0.14475311 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.041336425 = queryNorm
                0.1354154 = fieldWeight in 1616, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02734375 = fieldNorm(doc=1616)
          0.5 = coord(1/2)
      0.14285715 = coord(1/7)
    
    Abstract
    The information available in languages other than English in the World Wide Web is increasing significantly. According to a report from Computer Economics in 1999, 54% of Internet users are English speakers ("English Will Dominate Web for Only Three More Years," Computer Economics, July 9, 1999, http://www.computereconomics. com/new4/pr/pr990610.html). However, it is predicted that there will be only 60% increase in Internet users among English speakers verses a 150% growth among nonEnglish speakers for the next five years. By 2005, 57% of Internet users will be non-English speakers. A report by CNN.com in 2000 showed that the number of Internet users in China had been increased from 8.9 million to 16.9 million from January to June in 2000 ("Report: China Internet users double to 17 million," CNN.com, July, 2000, http://cnn.org/2000/TECH/computing/07/27/ china.internet.reut/index.html). According to Nielsen/ NetRatings, there was a dramatic leap from 22.5 millions to 56.6 millions Internet users from 2001 to 2002. China had become the second largest global at-home Internet population in 2002 (US's Internet population was 166 millions) (Robyn Greenspan, "China Pulls Ahead of Japan," Internet.com, April 22, 2002, http://cyberatias.internet.com/big-picture/geographics/article/0,,5911_1013841,00. html). All of the evidences reveal the importance of crosslingual research to satisfy the needs in the near future. Digital library research has been focusing in structural and semantic interoperability in the past. Searching and retrieving objects across variations in protocols, formats and disciplines are widely explored (Schatz, B., & Chen, H. (1999). Digital libraries: technological advances and social impacts. IEEE Computer, Special Issue an Digital Libraries, February, 32(2), 45-50.; Chen, H., Yen, J., & Yang, C.C. (1999). International activities: development of Asian digital libraries. IEEE Computer, Special Issue an Digital Libraries, 32(2), 48-49.). However, research in crossing language boundaries, especially across European languages and Oriental languages, is still in the initial stage. In this proposal, we put our focus an cross-lingual semantic interoperability by developing automatic generation of a cross-lingual thesaurus based an English/Chinese parallel corpus. When the searchers encounter retrieval problems, Professional librarians usually consult the thesaurus to identify other relevant vocabularies. In the problem of searching across language boundaries, a cross-lingual thesaurus, which is generated by co-occurrence analysis and Hopfield network, can be used to generate additional semantically relevant terms that cannot be obtained from dictionary. In particular, the automatically generated cross-lingual thesaurus is able to capture the unknown words that do not exist in a dictionary, such as names of persons, organizations, and events. Due to Hong Kong's unique history background, both English and Chinese are used as official languages in all legal documents. Therefore, English/Chinese cross-lingual information retrieval is critical for applications in courts and the government. In this paper, we develop an automatic thesaurus by the Hopfield network based an a parallel corpus collected from the Web site of the Department of Justice of the Hong Kong Special Administrative Region (HKSAR) Government. Experiments are conducted to measure the precision and recall of the automatic generated English/Chinese thesaurus. The result Shows that such thesaurus is a promising tool to retrieve relevant terms, especially in the language that is not the same as the input term. The direct translation of the input term can also be retrieved in most of the cases.