| tech,9-2-H01-1040,bq | information is used in a <term> prototype | system | </term> designed to support <term> information | #323 We describe how this information is used in a prototype system designed to support information workers' access to a pharmaceutical news archive as part of their industry watch function. |
| tech,13-3-H01-1040,bq | qualitative user evaluation </term> of the <term> | system | </term> , which while broadly positive indicates | #357 We also report results of a preliminary, qualitative user evaluation of thesystem, 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,10-1-H01-1041,bq | <term> Korean-to-English machine translation | system | </term><term> CCLINC ( Common Coalition Language | #399 At MIT Lincoln Laboratory, we have been developing a Korean-to-English machine translation system CCLINC (Common Coalition Language System at Lincoln Laboratory). |
| tool,1-2-H01-1041,bq | <term> CCLINC Korean-to-English translation | system | </term> consists of two <term> core modules | #415 The CCLINC Korean-to-English translation system consists of two core modules, language understanding and generation modules mediated by a language neutral meaning representation called a semantic frame. |
| tech,5-3-H01-1041,bq | frame </term> . The key features of the <term> | system | </term> include : ( i ) Robust efficient <term> | #444 The key features of thesystem include: (i) Robust efficient parsing of Korean (a verb final language with overt case markers, relatively free word order, and frequent omissions of arguments). |
| tech,3-5-H01-1041,bq | target language </term> . ( iii ) <term> Rapid | system | development </term> and porting to new <term> | #501 (iii) Rapid system development and porting to new domains via knowledge-based automated acquisition of grammars. |
| tech,15-6-H01-1041,bq | chemical biological warfare , the <term> | system | </term> produces the <term> translation output | #530 Having been trained on Korean newspaper articles on missiles and chemical biological warfare, thesystem produces the translation output sufficient for content understanding of the original document. |
| tech,3-2-H01-1049,bq | integrate a <term> spoken language understanding | system | </term> with <term> intelligent mobile agents | #801 We integrate a spoken language understanding system with intelligent mobile agents that mediate between users and information sources. |
| personnel can converse with their logistics | system | to place a supply or information request | #838 Using LCS-Marine, tactical personnel can converse with their logistics system to place a supply or information request. | |
| tech,5-6-H01-1049,bq | Requestors </term> can also instruct the <term> | system | </term> to notify them when the status of | #869 Requestors can also instruct thesystem to notify them when the status of a request changes or when a request is complete. |
| other,3-3-H01-1055,bq | the <term> user </term> . The issue of <term> | system | response </term> to <term> users </term> has | #971 The issue ofsystem response to users has been extensively studied by the natural language generation community, though rarely in the context of dialog systems. |
| measure(ment),7-2-H01-1068,bq | measure <term> user satisfaction </term> , <term> | system | support of mission success </term> and <term> | #1214 The three tiers measure user satisfaction,system support of mission success and component performance. |
| tech,23-1-P01-1004,bq | performance </term> of a <term> translation memory | system | </term> . We take a selection of both <term> | #1486 In this paper, we compare the relative effects of segment order, segmentation and segment contiguity on the retrieval performance of a translation memory system. |
| tech,12-2-P01-1056,bq | planner </term> for a <term> spoken dialogue | system | </term> by eliciting <term> subjective human | #2064 In this paper We experimentally evaluate a trainable sentence planner for a spoken dialogue system by eliciting subjective human judgments. |
| tech,22-4-P01-1056,bq | </term> , and as well as the <term> hand-crafted | system | </term> . We describe a set of <term> supervised | #2122 We show that the trainable sentence planner performs better than the rule-based systems and the baselines, and as well as the hand-crafted system. |
| other,11-4-N03-1001,bq | on three different <term> spoken language | system | domains </term> . Motivated by the success | #2303 The classification accuracy of the method is evaluated on three different spoken language system domains. |
| other,17-4-N03-1004,bq | relative improvement over our <term> baseline | system | </term> in the number of <term> questions correctly | #2414 Experiments evaluating the effectiveness of our answer resolution algorithm show a 35.0% relative improvement over our baseline system in the number of questions correctly answered, and a 32.8% improvement according to the average precision metric. |
| paper we present <term> ONTOSCORE </term> , a | system | for scoring sets of <term> concepts </term> | #2443 In this paper we present ONTOSCORE, a system for scoring sets of concepts on the basis of an ontology. | |
| tech,3-2-N03-1012,bq | <term> ontology </term> . We apply our <term> | system | </term> to the task of <term> scoring </term> | #2459 We apply oursystem to the task of scoring alternative speech recognition hypotheses (SRH) in terms of their semantic coherence. |
| tech,4-4-N03-1012,bq | hypotheses </term> . An evaluation of our <term> | system | </term> against the <term> annotated data </term> | #2505 An evaluation of oursystem against the annotated data shows that, it successfully classifies 73.2% in a German corpus of 2.284 SRHs as either coherent or incoherent (given a baseline of 54.55%). |
