Next Article in Journal
Impact of Inulin Addition on Properties of Natural Yogurt
Next Article in Special Issue
A Polarity Capturing Sphere for Word to Vector Representation
Previous Article in Journal
Potential Acetylcholinesterase, Lipase, α-Glucosidase, and α-Amylase Inhibitory Activity, as well as Antimicrobial Activities, of Essential Oil from Lettuce Leaf Basil (Ocimum basilicum L.) Elicited with Jasmonic Acid
Previous Article in Special Issue
Paraphrase Identification with Lexical, Syntactic and Sentential Encodings
Open AccessArticle

Improving Sentence Retrieval Using Sequence Similarity

Faculty of Mechanical Engineering, Computing and Electrical Engineering, University of Mostar, 88000 Mostar, Bosnia and Herzegovina
Institute for Software Technology, German Aerospace Center, 28199 Bremen, Germany
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, 21000 Split, Croatia
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(12), 4316;
Received: 1 June 2020 / Revised: 17 June 2020 / Accepted: 19 June 2020 / Published: 23 June 2020
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. View Full-Text
Keywords: sentence retrieval; TF−ISF; BM25; language modeling; partial match; sequence similarity sentence retrieval; TF−ISF; BM25; language modeling; partial match; sequence similarity
Show Figures

Figure 1

MDPI and ACS Style

Boban, I.; Doko, A.; Gotovac, S. Improving Sentence Retrieval Using Sequence Similarity. Appl. Sci. 2020, 10, 4316.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Search more from Scilit
Back to TopTop