Preserving the user’s preference in document-category management is essential because it affects his/her search efficiency, cognitive processing load, and satisfaction. Prior research has investigated automated document category evolution by using lexicon-based documentcategory evolution techniques which take into account the document categories previously created by the user. However, comparin...

Domain specific words and ontological information among words are important resources for general natural language applications. This paper proposes a statistical model for finding domain specific words (DSW s) in particular domains, and thus building the association among them. When applying this model to the hierarchical structure of the web directories node-by-node, the document tree can pot...

In this paper we present the results of two experiments. The first is on the categorization of texture words in the English language. The goal was to determine whether there is a common basis for subjects’ groupings of words related to visual texture, and if so, to identify the underlying dimensions used to categorize those words. Eleven major clusters were identified through hierarchical clust...

Taking Mandarin Possessive Construction (MPC) as an example, the present study investigates the relation between lexicon and constructional schemas in a quantitative corpus linguistic approach. We argue that the wide use of raw frequency distribution in traditional corpus linguistic studies may undermine the validity of the results and reduce the possibility for interdisciplinary communication....

Since the 1960s, much research has addressed the issue of how the two languages of a bilingual are cognitively represented. This early research, mostly during the 1960s and 1970s, posed the question as one versus two separate stores. Not all, but a large part of these studies focused specifically on the organization of the lexicon and these will be concerned here. Some researchers suggested ent...

We propose a novel method to predict the interparagraph discourse structure of text, i.e. to infer which paragraphs are related to each other and form larger segments on a higher level. Our method combines a clustering algorithm with a model of segment “relatedness” acquired in a machine learning step. The model integrates information from a variety of sources, such as word co-occurrence, lexic...

Large-scale knowledge-based machine translation requires significant amounts of lexical knowledge in order to map syntactic structures to conceptual structures. Tfiis paper presents a framework in which lexical knowledge is separated into different levels of representation, which are arranged in a hierarchical model based on principles of knowledge representation and lexical semantics. The prop...

We have constructed the IPA Lexicon of Basic Japanese Nouns (IPAL-BN), which has a hierarchical structure based on the syntactic and semantic properties of no,ms. In our lexicon, each lexical entry consists of subentries, and subentries have semantic property information. Among these elements, we focus here on the subentry description. Conventional Japanese dictionaries only enmnerate various u...