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Table 1 Index terms list

in Downloaded from
by Yen-liang Chen, Jhong-jhih Wei, Shin-yi Wu, Ya-han Hu, Yen-liang Chen, Jhong-jhih Wei, Shin-yi Wu 2005
"... In PAGE 13: ... The results are shown in Table 11. In Table1 0, the results indicate that the proposed algorithm outperforms the other two algorithms in all situations. Among these three algorithms, ANN outper- forms SW, and SW outperforms GM.... ..."

Table 4: Measures of index term complexity

in Toward a Task-based Gold Standard for Evaluation of NP Chunks and Technical Terms
by Nina Wacholder
"... In PAGE 5: ...3%. Why did the subjects demonstrate such a strong preference for the human terms? Table4 illustrates some important differences between the human terms and the automatically identified terms. The terms selected on are longer, as measured in number of words, and more complex, as measured by number of prepositions per index terms and by number of con- tent-bearing words.... ..."

Table 2. Average Index Terms per Document

in Improving Document Representations Using Relevance Feedback: The RFA Algorithm
by Razvan Stefan Bot 2004
"... In PAGE 6: ... 5.1 Dimensionality Reduction The results presented in Table2 , show that RFA reduces the dimensionality of the affected documents space to a great extent. The reduction is obtained while preserving or improving the retrieval effectiveness of the system augmented with RFA (see results in Sections 5.... In PAGE 6: ... The retrieval systems ST, BR, BB and BS are considered together since none of them possesses a dimensionality reduction technique. In fact for the BR, BB and BS systems the dimensionality is even higher than the one presented in Table2 , because of the introduction of new terms. First column of Table 2 shows the minimum dimensionality, which in fact corresponds to the ST system.... In PAGE 6: ... In fact for the BR, BB and BS systems the dimensionality is even higher than the one presented in Table 2, because of the introduction of new terms. First column of Table2 shows the minimum dimensionality, which in fact corresponds to the ST system. 5.... ..."
Cited by 1

Table 1: Indexing terms tested by participating teams.

in Evaluating Arabic Retrieval from English or French Queries:
by The Trec- Cross-Language, Douglas W. Oard, Fredric C. Gey, Bonnie J. Dorr 2002
Cited by 1

Table 1. Index terms and specific words

in Measuring Generality of Documents
by Hyun Woong Shin, Eduard Hovy, Dennis Mcleod, Larry Pryor
"... In PAGE 2: ... Domain dependent ontology In order to generate the proper degree of generality, we analyzed the underlying corpus. Table1 depicts the total ... ..."

Table 5.3: Index terms generated

in NLP-Supported Full-Text Retrieval
by Michael Piotrowski

Table 2 Examples of indexing terms for di erent subword units. Subword Unit Indexing Terms

in Subword-based Approaches for Spoken Document Retrieval
by Kenney Ng, Victor W. Zue
"... In PAGE 13: ... The subwords are derived from clean phonetic transcriptions of the spoken documents. phone sequence subword units for the phrase \weather forecast quot; are given in Table2 . For large enough n, we see that cross-word constraints can be captured by these units (e.... In PAGE 15: ... In particular, the threshold had to be increased in order to include the ay and oy phones in the c=20 class set. Ex- amples of some broad class subword units (class c=20, length n=4) are given in Table2 . For the NPR spoken document set, the number of unique broad class subword units (c=20, n=4) derived from clean phonetic transcriptions of the speech is 35265 out of a total of cn =204 = 160000 possibilities.... In PAGE 17: ...nd words, i.e., syllables [5]. Syllabic units were generated for the speech mes- sages and queries using these rules, treating the message/query as one long phone sequence with no word boundary information. Examples of some syl- labic subword units are given in Table2 . For the NPR spoken document set, the number of unique syllable units derived from clean phonetic transcriptions of the speech is 5475.... ..."

Table 2. MMI Index Terms at HSTAT Source Level

in Hierarchical concept indexing of full-text documents
by Lawrence W. Wright, Holly K. Grossetta Nardini, Alan R. Aronson, Thomas C. Rindflesch 1999
"... In PAGE 11: ...terms. Table2 provides a summary of the resulting source indexing terms, grouped by indexing level and vocabulary. In general characteristics, the MMI indexes look attractive as an alternative compact represen- tation of source subject coverage.... ..."
Cited by 8

Table 1. Number of index terms extracted from the CLEF corpus

in On the usefulness of extracting syntactic dependencies for text indexing
by Miguel A. Alonso, Jesús Vilares, Víctor M. Darriba 2002
"... In PAGE 6: ... Moreover, the employment of nite-state techniques in the implementation of our methods let us to reduce their computational cost, making possible their application in practical environments. Table1 shows the statistics of the terms that compose the corpus. The rst and second row show the total number of terms and unique terms obtained for the indexed documents, respectively, either for the source text and for the di erent con ated texts.... ..."
Cited by 8

Table 1. Number of index terms extracted from the CLEF corpus

in On the Usefulness of Extracting Syntactic Dependencies for Text Indexing
by Miguel A. Alonso, Jesús Vilares, Víctor M. Darriba
"... In PAGE 6: ... Moreover, the employment of nite-state techniques in the implementation of our methods let us to reduce their computational cost, making possible their application in practical environments. Table1 shows the statistics of the terms that compose the corpus. The rst and second row show the total number of terms and unique terms obtained for the indexed documents, respectively, either for the source text and for the di erent con ated texts.... ..."
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