Snippet generation using LAIR (Local Alignment for Information Retrieval)

Date

2023-6-23

Author

Yılmaz, Mert Anıl

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

84
views

124
downloads

Cite This

The main objective of this thesis is to show the extraction of sections relevant to a query from ranked documents in the form of a snippet (summary). To achieve this, we adapt the local sequence alignment method, commonly used in bioinformatics to identify similarities between gene sequences. By applying this method in information retrieval, we can spot the relevant sections within the ranked documents. To address the shortcomings of this approach in terms of data processing, including time and computational power, we reduce them to a negligible level by applying the method to only relevant documents. The quality of the snippets is assessed by employing various metrics and they are compared with Google snippets. In addition, the benefits of the local sequence alignment method are emphasized by adapting this method to query searches in YouTube videos.

Subject Keywords

Information retrieval, Bioinformatics, Local sequence alignment, Snippet generation

URI

https://hdl.handle.net/11511/104492

Collections

Graduate School of Natural and Applied Sciences, Thesis