In this report two programs for statistical analysis of concordance lines are described. The programs have been developed for analysing the lexical context of a given word. It is shown how different parameter settings influence the outcome of collocational analysis, and how the concept of collocation can be extended to allow the extraction of lines typical for a word from a set of concordance l...

This paper presents a Natural Language Processing (NLP) approach to filter Named Entities (NE) from a list of collocation candidates. The NE are defined as the names of ’People’, ’Places’, ’Organizations’, ’Software’, ’Illnesses’, and so forth. The proposed method is based on statistical measures associated with Web resources to identify NE. Our method has three stages: (1) Building artificial ...

Selecting the word translation from a set of target language words, one that conveys the correct sense of source word and makes more fluent target language output, is one of core problems in machine translation. In this paper we compare the 3 methods of estimating word translation probabilities for selecting the translation word in Thai – English Machine Translation. The 3 methods are (1) Metho...

A key data preparation step in Text Mining, Term Extraction selects the terms, or collocation of words, attached to specific concepts. In this paper, the task of extracting relevant collocations is achieved through a supervised learning algorithm, exploiting a few collocations manually labelled as relevant/irrelevant. The candidate terms are described along 13 standard statistical criteria meas...

Once Indonesian students translate collocation into English, they remain under their culture and language system. This qualitative research intends to identify that translated inappropriately English explain how intervene in translation. A list of some sentences containing was by the students. The differences lies way lexical choice is inappropriate. Both dictionaries were used reflect meaning ...

In this talk we describe the language component of FASTY, a text prediction system designed to improve text input efficiency for disabled users.1 The FASTY language component is based on state-of-the-art n-grambased word-level and Part-of-Speech-level prediction and on a number of innovative modules (morphological analysis, collocation-based prediction, compound prediction) that are meant to en...

The Semantic Knowledge-base of Contemporary Chinese (SKCC) is a large scale Chinese semantic resource developed by the Institute of Computational Linguistics of Peking University. It provides a large amount of semantic information such as semantic hierarchy and collocation features for 66,539 Chinese words and their English counterparts. Its POS and semantic classification represent the latest ...

Given a noisy text page, a word recognizer can generate a set of candidates for each word image. A relaxation algorithm was proposed previously by the authors that uses word collocation statistics to select the candidate for each word that has the highest probability of being the correct decision. Because word collocation is a local constraint and collocation data trained from corpora are usual...