%0 Conference Paper %1 Torbati_2020 %A Torbati, Ghazaleh H. %A Yates, Andrew %A Weikum, Gerhard %B Proceedings of the 2020 Conference on Human Information Interaction and Retrieval %D 2020 %I ACM %K adaptive-search chiir2020 open-user-model scrutability %P 427-431 %R 10.1145/3343413.3378011 %T Personalized Entity Search by Sparse and Scrutable User Profiles %U https://doi.org/10.1145%2F3343413.3378011 %X Prior work on personalizing web search results has focused on considering query-and-click logs to capture users' individual interests. For product search, extensive user histories about purchases and ratings have been exploited. However, for general entity search, such as for books on specific topics or travel destinations with certain features, personalization is largely underexplored. In this paper, we address personalization of book search, as an exemplary case of entity search, by exploiting sparse user profiles obtained through online questionnaires. We devise and compare a variety of re-ranking methods based on language models or neural learning. Our experiments show that even very sparse information about individuals can enhance the effectiveness of the search results.

@inproceedings{Torbati_2020, abstract = {Prior work on personalizing web search results has focused on considering query-and-click logs to capture users' individual interests. For product search, extensive user histories about purchases and ratings have been exploited. However, for general entity search, such as for books on specific topics or travel destinations with certain features, personalization is largely underexplored. In this paper, we address personalization of book search, as an exemplary case of entity search, by exploiting sparse user profiles obtained through online questionnaires. We devise and compare a variety of re-ranking methods based on language models or neural learning. Our experiments show that even very sparse information about individuals can enhance the effectiveness of the search results. }, added-at = {2020-11-23T00:46:17.000+0100}, author = {Torbati, Ghazaleh H. and Yates, Andrew and Weikum, Gerhard}, biburl = {https://www.bibsonomy.org/bibtex/2a7aa8a234efc2f07dcbf2770f3c43dcb/brusilovsky}, booktitle = {Proceedings of the 2020 Conference on Human Information Interaction and Retrieval}, description = {Personalized Entity Search by Sparse and Scrutable User Profiles | Proceedings of the 2020 Conference on Human Information Interaction and Retrieval}, doi = {10.1145/3343413.3378011}, interhash = {6f24b63b60db9db736607d96aba0e1a3}, intrahash = {a7aa8a234efc2f07dcbf2770f3c43dcb}, keywords = {adaptive-search chiir2020 open-user-model scrutability}, month = mar, pages = {427-431}, publisher = {{ACM}}, timestamp = {2020-11-23T00:50:25.000+0100}, title = {Personalized Entity Search by Sparse and Scrutable User Profiles}, url = {https://doi.org/10.1145%2F3343413.3378011}, year = 2020 }