scholarly journals Sentence Retrieval using Stemming and Lemmatization with Different Length of the Queries

2020 ◽  
Vol 5 (3) ◽  
pp. 349-354 ◽  
Author(s):  
Ivan Boban ◽  
Alen Doko ◽  
Sven Gotovac
Keyword(s):  
Sentence Retrieval

Aspects of sentence retrieval

2007 ◽  
Vol 41 (2) ◽  
pp. 127-127 ◽  
Author(s):  
Vanessa Murdock
Keyword(s):  
Sentence Retrieval

scholarly journals Exploration of term dependence in sentence retrieval

2007 ◽  
Author(s):  
Keke Cai ◽  
Jiajun Bu ◽  
Chun Chen ◽  
Kangmiao Liu
Keyword(s):  
Sentence Retrieval

scholarly journals Improving Sentence Retrieval Using Sequence Similarity

2020 ◽  
Vol 10 (12) ◽  
pp. 4316 ◽  
Author(s):  
Ivan Boban ◽  
Alen Doko ◽  
Sven Gotovac
Keyword(s):  
Question Answering ◽  
Sequence Similarity ◽  
Novelty Detection ◽  
Document Retrieval ◽  
Language Modeling ◽  
Information Need ◽  
Partial Matching ◽  
Retrieval Technique ◽  
Sentence Retrieval ◽  
Using Data

Sentence retrieval is an information retrieval technique that aims to find sentences corresponding to an information need. It is used for tasks like question answering (QA) or novelty detection. Since it is similar to document retrieval but with a smaller unit of retrieval, methods for document retrieval are also used for sentence retrieval like term frequency—inverse document frequency (TF-IDF), BM 25 , and language modeling-based methods. The effect of partial matching of words to sentence retrieval is an issue that has not been analyzed. We think that there is a substantial potential for the improvement of sentence retrieval methods if we consider this approach. We adapted TF-ISF, BM 25 , and language modeling-based methods to test the partial matching of terms through combining sentence retrieval with sequence similarity, which allows matching of words that are similar but not identical. All tests were conducted using data from the novelty tracks of the Text Retrieval Conference (TREC). The scope of this paper was to find out if such approach is generally beneficial to sentence retrieval. However, we did not examine in depth how partial matching helps or hinders the finding of relevant sentences.

Bidirectional image-sentence retrieval by local and global deep matching

2019 ◽  
Vol 345 ◽  
pp. 36-44 ◽  
Author(s):  
Lin Ma ◽  
Wenhao Jiang ◽  
Zequn Jie ◽  
Xu Wang
Keyword(s):  
Sentence Retrieval

scholarly journals BELTracker: evidence sentence retrieval for BEL statements

Database ◽  
2016 ◽  
Vol 2016 ◽  
pp. baw079 ◽  
Author(s):  
Majid Rastegar-Mojarad ◽  
Ravikumar Komandur Elayavilli ◽  
Hongfang Liu
Keyword(s):  
Sentence Retrieval
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