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Table 3: Results of content-based evaluation

in
by unknown authors
"... In PAGE 4: ... Ten systems, including a base- line system, participated in this evaluation. Second, we show the results of the content-based evaluation in Table3 . The results also show the average values of the 30 summaries by the system.... ..."

Table 1: Content-based retrieval on images.

in The webspace method: On the integration of database technology with information retrieval
by Roelof Van Zwol, Peter M. G. Apers 2000
"... In PAGE 5: ... The rst query we discuss, shows how content-based querying of images is integrated in the webspace system. The SQL-query shown in Table1 .a queries the images contained in the webspace, based on their similarity.... In PAGE 5: ... The similarity is based on the distance between the rgb- and hsb-histograms derived from the images, given a sample image. The query results are displayed in Table1 .b.... ..."
Cited by 7

Table 10. Content-based evaluation

in Yet
by Kiyonori Ohtake, Daigo Okamoto, Mitsuru Kodama, Shigeru Masuyama

Table 4. Content-based Evaluation Results of the Task A2

in unknown title
by unknown authors
"... In PAGE 4: ...2 Task A2: Free summarization In the task A2, free summarization task, we submitted the summaries generated by sentence extraction with pat- terns to shorten the sentences. The content-based evaluation results of the task A2 are shown in Table4 . FREE sum- mary means the summary the human wrote freely except a restriction of the number of characters.... ..."

Table 4. Content-based Evaluation Results of the Task A2

in unknown title
by unknown authors
"... In PAGE 4: ...2 Task A2: Free summarization In the task A2, free summarization task, we submitted the summaries generated by sentence extraction with pat- terns to shorten the sentences. The content-based evaluation results of the task A2 are shown in Table4 . FREE sum- mary means the summary the human wrote freely except a restriction of the number of characters.... ..."

Table VIII. Comparison by Content-based Image Retrieval

in A NOVEL APPROACH TO COLOR NORMALIZATION USING NEURAL NETWORK
by H. D. Cheng, Xiaopeng Cai, Rui Min

Table 10: Statistical significance of the results for the training set in the comparison of content-based and semantic features. Content-based features are proved better

in Semantic Classification 1
by Anastasia Krithara 2004

Table 11: Macro F1 gains of GP over content-based SVM and combination-based SVM

in A Novel Hybrid Focused Crawling Algorithm to Build Domain-Specific Collections
by Yuxin Chen, Edward A. Fox, Weiguo Fan, Chang-tien Lu, Naren Ramakrishnan, Ricardo Da Silva Torres, Yuxin Chen 2007
"... In PAGE 7: ...ased SVM on the 30% sample ........................................................................................ 54 Table11 : Macro F1 gains of GP over content-based SVM and combination-based SVM .... ..."

Table 1. A case-like description of a lm for content-based recommendation.

in Concept Discovery in Collaborative Recommender Systems
by Patrick Clerkin, Padraig Cunningham, Conor Hayes 2003
"... In PAGE 1: ...1 Content-based recommendation Here we will describe a CBR-like content-based recommendation system that we can use for comparison purposes. Table1 shows a case-like description of a lm (movie) and Table 2 shows the corresponding description of a user of the recommendation system. In this scenario recommendation is based on how well a lm matches a users pro le.... ..."
Cited by 1

Table 1: F1 scores of collaborative and content-based categorization. # Training examples

in Semi-Supervised Collaborative Text Classification
by Rong Jin, Ming Wu, Rahul Sukthankar
"... In PAGE 5: ... This raises the concern that the user feedback representation may be less rich than the keyword representation and thus col- laborative text categorization may not be as efiective as content-based text cat- egorization. We summarize in Table1 the F1 results for both collaborative text categorization and content-based text categorization. In all cases, collaborative text categorization is considerably more efiective.... ..."
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