| <term> Oral communication </term> is ubiquitous and carries important information yet it is also time consuming to document . | #7 Oral communication is ubiquitous and carries important information yet it is also time consuming to document. | |
| The question is , however , how an interesting information piece would be found in a <term> large database </term> . | #45 The question is, however, how an interesting information piece would be found in a large database. | |
| tech,1-4-H01-1001,bq | Traditional <term> information retrieval techniques </term> use a <term> histogram </term> of <term> keywords </term> as the <term> document representation </term> but <term> oral communication </term> may offer additional <term> indices </term> such as the time and place of the rejoinder and the attendance . | #56 Traditionalinformation retrieval techniques use a histogram of keywords as the document representation but oral communication may offer additional indices such as the time and place of the rejoinder and the attendance. |
| tech,10-1-H01-1040,bq | In this paper we show how two standard outputs from <term> information extraction ( IE ) systems </term> - <term> named entity annotations </term> and <term> scenario templates </term> - can be used to enhance access to <term> text collections </term> via a standard <term> text browser </term> . | #284 In this paper we show how two standard outputs frominformation extraction (IE) systems - named entity annotations and scenario templates - can be used to enhance access to text collections via a standard text browser. |
| We describe how this information is used in a <term> prototype system </term> designed to support <term> information workers </term> ' access to a <term> pharmaceutical news archive </term> as part of their <term> industry watch </term> function . | #317 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. | |
| other,14-2-H01-1040,bq | We describe how this information is used in a <term> prototype system </term> designed to support <term> information workers </term> ' access to a <term> pharmaceutical news archive </term> as part of their <term> industry watch </term> function . | #327 We describe how this information is used in a prototype system designed to supportinformation workers' access to a pharmaceutical news archive as part of their industry watch function. |
| We believe that these <term> evaluation techniques </term> will provide information about both the <term> human language learning process </term> , the <term> translation process </term> and the <term> development </term> of <term> machine translation systems </term> . | #589 We believe that these evaluation techniques will provide information about both the human language learning process, the translation process and the development of machine translation systems. | |
| other,16-2-H01-1049,bq | We integrate a <term> spoken language understanding system </term> with <term> intelligent mobile agents </term> that mediate between <term> users </term> and <term> information sources </term> . | #811 We integrate a spoken language understanding system with intelligent mobile agents that mediate between users andinformation sources. |
| Using <term> LCS-Marine </term> , tactical personnel can converse with their logistics system to place a supply or information request . | #844 Using LCS-Marine, tactical personnel can converse with their logistics system to place a supply or information request. | |
| measure(ment),7-2-H01-1070,bq | The paper also proposes <term> rule-reduction algorithm </term> applying <term> mutual information </term> to reduce the <term> error-correction rules </term> . | #1270 The paper also proposes rule-reduction algorithm applying mutual information to reduce the error-correction rules. |
| The <term> TAP-XL Automated Analyst 's Assistant </term> is an application designed to help an <term> English-speaking </term> analyst write a <term> topical report </term> , culling information from a large inflow of <term> multilingual , multimedia data </term> . | #3593 The TAP-XL Automated Analyst's Assistant is an application designed to help an English-speaking analyst write a topical report, culling information from a large inflow of multilingual, multimedia data. | |
| tech,13-2-P03-1030,bq | In this paper we formulate <term> story link detection </term> and <term> new event detection </term> as <term> information retrieval task </term> and hypothesize on the impact of <term> precision </term> and <term> recall </term> on both <term> systems </term> . | #4076 In this paper we formulate story link detection and new event detection asinformation retrieval task and hypothesize on the impact of precision and recall on both systems. |
| other,11-5-P03-1031,bq | This paper proposes a method for resolving this <term> ambiguity </term> based on <term> statistical information </term> obtained from <term> dialogue corpora </term> . | #4228 This paper proposes a method for resolving this ambiguity based on statistical information obtained from dialogue corpora. |
| tool,10-6-P03-1033,bq | <term> Dialogue strategies </term> based on the <term> user modeling </term> are implemented in <term> Kyoto city bus information system </term> that has been developed at our laboratory . | #4393 Dialogue strategies based on the user modeling are implemented in Kyoto city bus information system that has been developed at our laboratory. |
| tech,3-7-P03-1050,bq | <term> Task-based evaluation </term> using <term> Arabic information retrieval </term> indicates an improvement of 22-38 % in <term> average precision </term> over <term> unstemmed text </term> , and 96 % of the performance of the proprietary <term> stemmer </term> above . | #4573 Task-based evaluation using Arabic information retrieval indicates an improvement of 22-38% in average precision over unstemmed text, and 96% of the performance of the proprietary stemmer above. |
| tech,19-1-P03-1068,bq | We describe the ongoing construction of a large , <term> semantically annotated corpus </term> resource as reliable basis for the large-scale <term> acquisition of word-semantic information </term> , e.g. the construction of <term> domain-independent lexica </term> . | #4954 We describe the ongoing construction of a large, semantically annotated corpus resource as reliable basis for the large-scale acquisition of word-semantic information, e.g. the construction of domain-independent lexica. |
| other,26-4-C04-1068,bq | We tested the <term> clustering and filtering processes </term> on <term> electronic newsgroup discussions </term> , and evaluated their performance by means of two experiments : coarse-level <term> clustering </term> and simple <term> information retrieval </term> . | #5477 We tested the clustering and filtering processes on electronic newsgroup discussions, and evaluated their performance by means of two experiments: coarse-level clustering and simpleinformation retrieval. |
| other,27-1-C04-1112,bq | In this paper , we present a <term> corpus-based supervised word sense disambiguation ( WSD ) system </term> for <term> Dutch </term> which combines <term> statistical classification ( maximum entropy ) </term> with <term> linguistic information </term> . | #6007 In this paper, we present a corpus-based supervised word sense disambiguation (WSD) system for Dutch which combines statistical classification (maximum entropy) with linguistic information. |
| other,12-3-N04-1022,bq | We describe a hierarchy of <term> loss functions </term> that incorporate different levels of <term> linguistic information </term> from <term> word strings </term> , <term> word-to-word alignments </term> from an <term> MT system </term> , and <term> syntactic structure </term> from <term> parse-trees </term> of <term> source and target language sentences </term> . | #6588 We describe a hierarchy of loss functions that incorporate different levels of linguistic information from word strings, word-to-word alignments from an MT system, and syntactic structure from parse-trees of source and target language sentences. |
| tech,1-4-N04-4028,bq | The <term> information extraction system </term> we evaluate is based on a <term> linear-chain conditional random field ( CRF ) </term> , a <term> probabilistic model </term> which has performed well on <term> information extraction tasks </term> because of its ability to capture arbitrary , overlapping <term> features </term> of the input in a <term> Markov model </term> . | #6812 Theinformation extraction system we evaluate is based on a linear-chain conditional random field (CRF), a probabilistic model which has performed well on information extraction tasks because of its ability to capture arbitrary, overlapping features of the input in a Markov model. |
