Searching for "Average Precision at n." – sorted by Relevance.
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Topical Crawling for Business Intelligence
- stemming (using Porter stemming algorithm [15]) and stoplisting. For a given N, we can average precision
- Cited by 9 (6 self) – Add To MetaCart
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The Impact of Named Entity Normalization on Information Retrieval for Question Answering
- using the Mean Reciprocal Rank (MRR), success at rank n (s@n), and average precision at n (p@n
- Cited by 1 (1 self) – Add To MetaCart
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Non-contiguous word sequences for information retrieval
- Precision@10 0.67101 0.65021 (-3.1%) 0.66293 (-1.2%) Table 3: Average Precision@n each set of candidate
- Cited by 1 (0 self) – Add To MetaCart
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Measuring the Effects of Data Corruption on Information Retrieval
- performance on the corrupted data we are interested in random variables such as noisy average precision, n
- Cited by 21 (1 self) – Add To MetaCart
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Using Syntactic Information in Handling Natural Language Queries for Extended Boolean Retrieval Model
- the average recall and precision for top n ranked documents. The automatic boolean queries again shows better
- Cited by 3 (0 self) – Add To MetaCart
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An Interactive Chinese to English Retrieval System
- Chinese track data. Chinese manual ad hoc runs produced average precision (N=1000 documents) above 0
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Dedicated backing-off distributions for language model based passage retrieval
- of retrieval performance by plotting the non-interpolated average precision at N documents against different
- Cited by 4 (4 self) – Add To MetaCart
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CINDOR TREC-9 English-Chinese Evaluation
- (average precision) for the set of TREC-6 queries and N=10 (48 runs). The highest performance is obtained
- Cited by 2 (0 self) – Add To MetaCart
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Multi-Scale Audio Indexing For Translingual Spoken Document Retrieval
- is evaluated in terms of noninterpolated average precision (nAP). For each topic, we average the nAP attained
- Cited by 2 (1 self) – Add To MetaCart
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Investigating Lexical Substitution Scoring for Subtitle Generation
- the uninterpolated recall-precision curve, defined as follows: �N i=1 P(i)T (i) average precision = �N T (i) � i=1 (2
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