A Corpus-Based Statistics-Oriented (CBSO) methodology, which is an attempt to avoid the drawbacks of traditional rule-based approaches and purely statistical approaches, is introduced in this paper. Rule-based approaches, with rules induced by human experts, had been the dominant paradigm in the natural language processing community. Such approaches, however, suffer from serious difficulties in knowledge acquisition in terms of cost and consistency. Therefore, it is very difficult for such systems to be scaled-up. Statistical methods, with the capability of automatically acquiring knowledge from corpora, are becoming more and more popular, in part, to amend the shortcomings of rule-based approaches. However, most simple statistical models, which adopt almost nothing from existing linguistic knowledge, often result in a large parameter space and, thus, require an unaffordably large training corpus for even well-justified linguistic phenomena. The corpus-based statistics-oriented (CBSO) approach is a compromise between the two extremes of the spectrum for knowledge acquisition. CBSO approach

This paper presents several useful computational tools and available resources to facilitate linguistic studies. For each computational tool, we demonstrate why it is useful and how can it be used for research. In addition, linguistic examples are given for illustration. First, a very useful searching engine, Key Word in Context (KWIC), is introduced. This tool can automatically extract linguistically significant patterns from large corpora and help linguists discover syntagmatic generalizations. Second, Dynamic Clustering and Hierarchical Clustering are introduced for identifying natural clusters of words or phrases in distribution. Third, statistical measures which could be used to measure the degree of cohesion and correlation among linguistic units are presented. These tools can help linguists identify the boundaries of lexical units. Fourth, alignment tools for aligning parallel texts at the word, sentence and structure levels are presented for linguists who do comparative studies...