應用區域敏感雜湊進行中文文獻分類之研究

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應用區域敏感雜湊進行中文文獻分類之研究

Classification of Chinese Document Corpora Using Locality Sensitive Hashing

謝祥榆 , Masters　　Advisor：陳宗天;何善輝　　

繁體中文

中文文獻分類；中文斷詞；區域敏感雜湊； Text Classification ； Chinese Tokenization ； Locality Sensitive Hashing ； Chinese Document Corpora

Abstract │ Reference (25) │ Times Cited (1) │ Altmetrics

Abstract 〈TOP〉

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Documents classification is an important technique that usually utilizes traditional text mining methods, which often involve several text pre-processing steps such as stop words removal and tokenization. However, text mining technique was developed to process English corpora, it is not directly applicable to process Chinese corpora. For example, terms or words are separated by leading and trailing spaces in English that makes the work of tokenizing English corpora straightforward. However, there are no spaces between words in Chinese corpora that makes tokenizing the Chinese corpora a daunting task. To overcome the difficulties of Chinese tokenization, we utilize an algorithm that doesn’t need tokenization called Locality Sensitive Hashing (LSH). It breaks a text file into strings (shinglings) of fixed length which is a language-neutral method.

We classified research papers from different research fields using LSH and VSM algorithm in conjunction with KNN method respectively, and compared their classification results. First, we collected 6 different topics, each topic includes 60 Chinese articles. And then we randomly chose 10 to 50 articles as the model training data, and the remaining articles as the test data. We calculated the accuracy of both classification methods and found their accuracy on par, which provides empirical evidence that the LSH algorithm could be used to classify Chinese papers properly.

Reference ( 25 ) 〈TOP〉

Andoni, A., & Indyk, P. (2006). Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions. Paper presented at the Foundations of Computer Science, 2006. FOCS'06. 47th Annual IEEE Symposium on.
連結：
Boyack, K. W., & Klavans, R. (2010). Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately? Journal of the American Society for Information Science and Technology, 61(12), 2389-2404.
連結：
Chowdhury, G. (2010). Introduction to modern information retrieval: Facet publishing.
連結：
Chum, O., Philbin, J., & Zisserman, A. (2008). Near Duplicate Image Detection: min-Hash and tf-idf Weighting. Paper presented at the BMVC.
連結：
Hubert, L., & Arabie, P. (1985). Comparing partitions. Journal of classification, 2(1), 193-218.
連結：

Times Cited (1) 〈TOP〉

李治平(2016)。應用區域敏感雜湊對文獻進行分類之研究。臺北大學資訊管理研究所學位論文。2016。1-92。

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