Abstract
The Web is a vast place and search engines are our sensory organs to perceive it. To be efficient, Web exploration ideally should have a high serendipity potential. We present a formalization of Web search as a linguistic transformation, evaluate its stability, and apply it to produce serendipity lattices, containing suggestions of term chains to be used as exploration paths. We show experimentally that these lattices conform to two of the three serendipity criteria: relatedness and unexpectedness.
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Notes
- 1.
Information objects obtained by the search engine or contained in the documents pointed to by the URLs can also include images, videos and other multimodal objects, in this paper we consider only textual objects.
- 2.
Double quotes are necessary for some search engines to avoid replacement of the English term due to spelling correction on the search engine side.
- 3.
Taken from the Corpus of Contemporary American English https://corpus.byu.edu/coca/.
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Acknowledgments
The authors would like to thank the staff of La Mètis for their precious help in implementing the algorithms and performing massive online searches.
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Haralambous, Y., N’zi, E.E. (2023). Salience-Induced Term-Driven Serendipitous Web Exploration. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2019. Lecture Notes in Computer Science, vol 13451. Springer, Cham. https://doi.org/10.1007/978-3-031-24337-0_18
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