| other,10-1-A97-1042,ak | identifying likely <term> topics </term> of <term> | texts | </term> by their position in the <term> text | #28747 This paper addresses the problem of identifying likely topics oftexts by their position in the text. | |
| other,16-1-A97-1042,ak | texts </term> by their position in the <term> | text | </term> . It describes the <term> automated | #28753 This paper addresses the problem of identifying likely topics of texts by their position in thetext. | |
| other,21-2-A97-1042,ak | of locating the likely positions of <term> | topic-bearing sentences | </term> based on <term> genre-specific regularities | #28776 It describes the automated training and evaluation of an Optimal Position Policy, a method of locating the likely positions oftopic-bearing sentences based on genre-specific regularities of discourse structure. | |
| other,25-2-A97-1042,ak | topic-bearing sentences </term> based on <term> | genre-specific regularities | </term> of <term> discourse structure </term> | #28780 It describes the automated training and evaluation of an Optimal Position Policy, a method of locating the likely positions of topic-bearing sentences based ongenre-specific regularities of discourse structure. | |
| other,28-2-A97-1042,ak | genre-specific regularities </term> of <term> | discourse structure | </term> . This method can be used in applications | #28783 It describes the automated training and evaluation of an Optimal Position Policy, a method of locating the likely positions of topic-bearing sentences based on genre-specific regularities ofdiscourse structure. | |
| other,8-1-A97-1042,ak | the problem of identifying likely <term> | topics | </term> of <term> texts </term> by their position | #28745 This paper addresses the problem of identifying likelytopics of texts by their position in the text. | |
| other,9-2-A97-1042,ak | training and evaluation </term> of an <term> | Optimal Position Policy | </term> , a method of locating the likely | #28764 It describes the automated training and evaluation of anOptimal Position Policy, a method of locating the likely positions of topic-bearing sentences based on genre-specific regularities of discourse structure. | |
| tech,12-3-A97-1042,ak | <term> information retrieval </term> , <term> | routing | </term> , and <term> text summarization </term> | #28798 This method can be used in applications such as information retrieval,routing, and text summarization. | |
| tech,15-3-A97-1042,ak | retrieval </term> , <term> routing </term> , and <term> | text summarization | </term> . We investigate the utility of an | #28801 This method can be used in applications such as information retrieval, routing, andtext summarization. | |
| tech,3-2-A97-1042,ak | <term> text </term> . It describes the <term> | automated training and evaluation | </term> of an <term> Optimal Position Policy | #28758 It describes theautomated training and evaluation of an Optimal Position Policy, a method of locating the likely positions of topic-bearing sentences based on genre-specific regularities of discourse structure. | |
| tech,9-3-A97-1042,ak | can be used in applications such as <term> | information retrieval | </term> , <term> routing </term> , and <term> text | #28795 This method can be used in applications such asinformation retrieval, routing, and text summarization. |
