Query Abandonment Prediction with Recurrent Neural Models of Mouse Cursor Movements

Lukas Brückner, Ioannis Arapakis, Luis A. Leiva

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

1 Sitaatiot (Scopus)
59 Lataukset (Pure)

Abstrakti

Most successful search queries do not result in a click if the user can satisfy their information needs directly on the SERP. Modeling query abandonment in the absence of click-through data is challenging because search engines must rely on other behavioral signals to understand the underlying search intent. We show that mouse cursor movements make a valuable, low-cost behavioral signal that can discriminate good and bad abandonment. We model mouse movements on SERPs using recurrent neural nets and explore several data representations that do not rely on expensive hand-crafted features and do not depend on a particular SERP structure. We also experiment with data resampling and augmentation techniques that we adopt for sequential data. Our results can help search providers to gauge user satisfaction for queries without clicks and ultimately contribute to a better understanding of search engine performance.

AlkuperäiskieliEnglanti
OtsikkoCIKM 2020 - Proceedings of the 29th ACM International Conference on Information and Knowledge Management
KustantajaACM
Sivut1969-1972
Sivumäärä4
ISBN (elektroninen)9781450368599
DOI - pysyväislinkit
TilaJulkaistu - 19 lokakuuta 2020
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaACM International Conference on Information and Knowledge Management - Virtual, Online, Irlanti
Kesto: 19 lokakuuta 202023 lokakuuta 2020
Konferenssinumero: 29

Conference

ConferenceACM International Conference on Information and Knowledge Management
LyhennettäCIKM
MaaIrlanti
KaupunkiVirtual, Online
Ajanjakso19/10/202023/10/2020

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