| tech,17-1-H92-1095,bq | <term> Language understanding </term> work at <term> Paramax </term> focuses on applying general-purpose <term> language understanding technology </term> to <term> spoken language understanding </term> , <term> text understanding </term> , and <term> document processing </term> , integrating <term> language understanding </term> with <term> speech recognition </term> , <term> knowledge-based information retrieval </term> and <term> image understanding </term> . | #19654 Language understanding work at Paramax focuses on applying general-purpose language understanding technology to spoken language understanding,text understanding, and document processing, integrating language understanding with speech recognition, knowledge-based information retrieval and image understanding. |
| tech,24-2-H94-1084,bq | Our <term> document understanding technology </term> is implemented in a system called <term> IDUS ( Intelligent Document Understanding System ) </term> , which creates the data for a <term> text retrieval application </term> and the <term> automatic generation of hypertext links </term> . | #21412 Our document understanding technology is implemented in a system called IDUS (Intelligent Document Understanding System), which creates the data for atext retrieval application and the automatic generation of hypertext links. |
| tech,3-1-C04-1116,bq | We present a <term> text mining method </term> for finding <term> synonymous expressions </term> based on the <term> distributional hypothesis </term> in a set of coherent <term> corpora </term> . | #6095 We present atext mining method for finding synonymous expressions based on the distributional hypothesis in a set of coherent corpora. |
| tech,24-5-P04-2010,bq | Although the system performs well within a limited textual domain , further research is needed to make it effective for <term> open-domain question answering </term> and <term> text summarisation </term> . | #7122 Although the system performs well within a limited textual domain, further research is needed to make it effective for open-domain question answering andtext summarisation. |
| tech,21-3-H94-1084,bq | This paper summarizes the areas of research during <term> IDUS </term> development where we have found the most benefit from the <term> integration </term> of <term> image and text understanding </term> . | #21446 This paper summarizes the areas of research during IDUS development where we have found the most benefit from the integration of image and text understanding. |
| lr,26-6-P03-1050,bq | Our <term> resource-frugal approach </term> results in 87.5 % <term> agreement </term> with a state of the art , proprietary <term> Arabic stemmer </term> built using <term> rules </term> , <term> affix lists </term> , and <term> human annotated text </term> , in addition to an <term> unsupervised component </term> . | #4560 Our resource-frugal approach results in 87.5% agreement with a state of the art, proprietary Arabic stemmer built using rules, affix lists, and human annotated text, in addition to an unsupervised component. |
| other,26-4-P04-2005,bq | Our method takes advantage of the different way in which <term> word senses </term> are lexicalised in <term> English </term> and <term> Chinese </term> , and also exploits the large amount of <term> Chinese text </term> available in <term> corpora </term> and on the <term> Web </term> . | #6985 Our method takes advantage of the different way in which word senses are lexicalised in English and Chinese, and also exploits the large amount of Chinese text available in corpora and on the Web. |
| other,13-1-P84-1078,bq | This report describes <term> Paul </term> , a <term> computer text generation system </term> designed to create <term> cohesive text </term> through the use of <term> lexical substitutions </term> . | #13758 This report describes Paul, a computer text generation system designed to create cohesive text through the use of lexical substitutions. |
| lr,20-3-I05-4010,bq | The resultant <term> bilingual corpus </term> , 10.4 M <term> English words </term> and 18.3 M <term> Chinese characters </term> , is an authoritative and comprehensive <term> text collection </term> covering the specific and special domain of HK laws . | #8272 The resultant bilingual corpus, 10.4M English words and 18.3M Chinese characters, is an authoritative and comprehensivetext collection covering the specific and special domain of HK laws. |
| tech,6-1-P84-1078,bq | This report describes <term> Paul </term> , a <term> computer text generation system </term> designed to create <term> cohesive text </term> through the use of <term> lexical substitutions </term> . | #13751 This report describes Paul, a computer text generation system designed to create cohesive text through the use of lexical substitutions. |
| other,24-1-N03-4010,bq | The <term> JAVELIN system </term> integrates a flexible , <term> planning-based architecture </term> with a variety of <term> language processing modules </term> to provide an <term> open-domain question answering capability </term> on <term> free text </term> . | #3660 The JAVELIN system integrates a flexible, planning-based architecture with a variety of language processing modules to provide an open-domain question answering capability on free text. |
| lr,19-2-N03-4010,bq | The demonstration will focus on how <term> JAVELIN </term> processes <term> questions </term> and retrieves the most likely <term> answer candidates </term> from the given <term> text corpus </term> . | #3681 The demonstration will focus on how JAVELIN processes questions and retrieves the most likely answer candidates from the giventext corpus. |
| tech,38-3-H01-1040,bq | We also report results of a preliminary , <term> qualitative user evaluation </term> of the <term> system </term> , which while broadly positive indicates further work needs to be done on the <term> interface </term> to make <term> users </term> aware of the increased potential of <term> IE-enhanced text browsers </term> . | #383 We also report results of a preliminary, qualitative user evaluation of the system, which while broadly positive indicates further work needs to be done on the interface to make users aware of the increased potential of IE-enhanced text browsers. |
| tech,15-2-N06-4001,bq | <term> InfoMagnets </term> aims at making <term> exploratory corpus analysis </term> accessible to researchers who are not experts in <term> text mining </term> . | #10891 InfoMagnets aims at making exploratory corpus analysis accessible to researchers who are not experts intext mining. |
| other,10-2-A88-1001,bq | <term> Multimedia answers </term> include <term> videodisc images </term> and heuristically-produced complete <term> sentences </term> in <term> text </term> or <term> text-to-speech form </term> . | #14892 Multimedia answers include videodisc images and heuristically-produced complete sentences intext or text-to-speech form. |
| other,13-1-P82-1035,bq | Most large <term> text-understanding systems </term> have been designed under the assumption that the input <term> text </term> will be in reasonably neat form , e.g. , <term> newspaper stories </term> and other <term> edited texts </term> . | #12957 Most large text-understanding systems have been designed under the assumption that the inputtext will be in reasonably neat form, e.g., newspaper stories and other edited texts. |
| lr-prod,15-3-H94-1014,bq | The models were constructed using a 5K <term> vocabulary </term> and trained using a 76 million <term> word </term><term> Wall Street Journal text corpus </term> . | #21260 The models were constructed using a 5K vocabulary and trained using a 76 million word Wall Street Journal text corpus. |
| other,35-1-I05-4010,bq | In this paper we present our recent work on harvesting <term> English-Chinese bitexts </term> of the laws of Hong Kong from the <term> Web </term> and aligning them to the <term> subparagraph </term> level via utilizing the <term> numbering system </term> in the <term> legal text hierarchy </term> . | #8239 In this paper we present our recent work on harvesting English-Chinese bitexts of the laws of Hong Kong from the Web and aligning them to the subparagraph level via utilizing the numbering system in the legal text hierarchy. |
| tech,8-1-C90-3072,bq | <term> Spelling-checkers </term> have become an integral part of most <term> text processing software </term> . | #16730 Spelling-checkers have become an integral part of mosttext processing software. |
| other,11-7-H01-1042,bq | Subjects were given a set of up to six extracts of <term> translated newswire text </term> . | #695 Subjects were given a set of up to six extracts of translated newswire text. |
