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Table 10. Comparative summary among the LSA based summarization Algorithms

Table 10 Comparative summary among the LSA based summarization Algorithms

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Table 3: V’ matrix In Table 3, sentence with higher value is selected. So, from concept (conO) sentences (sen1) and (sen2) are selected to be part of the summary. Two sentences are selected for demonstration purpose.
Table 3: V’ matrix In Table 3, sentence with higher value is selected. So, from concept (conO) sentences (sen1) and (sen2) are selected to be part of the summary. Two sentences are selected for demonstration purpose.
Table 5: V" matrix and length values 6.2. Topic Method
Table 5: V" matrix and length values 6.2. Topic Method
After preprocessing, the concept x concept matrix is created to find out the main topics. The concept that has common sentences is determined, and new cell values are set to the total of common sentence scores. In Table7, an example of concept x concept matrix is given.
After preprocessing, the concept x concept matrix is created to find out the main topics. The concept that has common sentences is determined, and new cell values are set to the total of common sentence scores. In Table7, an example of concept x concept matrix is given.
Table7: New concept x concept matrix
Table7: New concept x concept matrix
Table 4: V’ matrix after preprocessing In Table4, the average value for each concept is calculated. Then, the cell values which are less than or equal to the average are set to zero.
Table 4: V’ matrix after preprocessing In Table4, the average value for each concept is calculated. Then, the cell values which are less than or equal to the average are set to zero.
Table8: Strength values After calculating strength values step, the Gong and Liu's approach [9] is followed to collect the sentences from the preprocessed V’. In able9, senl with the highest value is selected from con0. Where one sentence is selected from each concept.
Table8: Strength values After calculating strength values step, the Gong and Liu's approach [9] is followed to collect the sentences from the preprocessed V’. In able9, senl with the highest value is selected from con0. Where one sentence is selected from each concept.
Table 9. V" matrix after preprocessing 7. COMPARATIVE SUMMARY AMONG THE LSA BASED SUMMARIZATION ALGORITHMS
Table 9. V" matrix after preprocessing 7. COMPARATIVE SUMMARY AMONG THE LSA BASED SUMMARIZATION ALGORITHMS
Related topics:
Computer ScienceInformation RetrievalNatural Language ProcessingLatent Semantic AnalysisAutomatic Summarization
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