Challenges in Search on Streaming Services: Netflix Case Study

We discuss salient challenges of building a search experience for a streaming media service such as Netflix. We provide an overview of the role of recommendations within the search context to aid content discovery and support searches for unavailable (out-of-catalog) entities. We also stress the importance of keystroke-level instant search experience, and the technical challenges associated with implementing it across different devices and languages for a global audience.Comment: 4 pages, 2 figure

Analysis of Instant Search Query Logs ∗

Instant search is a new search paradigm that shows results as a user types in a query. It has become increasingly popular in recent years due to its simplicity and power. In an instantsearch system, every keystroke from a user triggers a new request to the server. Therefore, its log has a richer content than that of a traditional search system, and previous log analysis research is not applicable to this type of log. In this paper, we study the problem of analyzing the query log of an instant-search system. We propose a classification scheme for user typing behaviors. We also compare the log of an instant-search system and that of a traditional search system on the same data. The results show that on a people directory search system, instant search can typically save 2 seconds per search, reduce the typing effort by showin

Analysis of Instant Search Query Logs ∗

Instant search is a new search paradigm that shows results as a user types in a query. It has become increasingly popular in recent years due to its simplicity and power. In an instantsearch system, every keystroke from a user triggers a new request to the server. Therefore, its log has a richer content than that of a traditional search system, and previous log analysis research is not applicable to this type of log. In this paper, we study the problem of analyzing the query log of an instant-search system. We propose a classification scheme for user typing behaviors. We also compare the log of an instant-search system and that of a traditional search system on the same data. The results show that on a people directory search system, instant search can typically save 2 seconds per search, reduce the typing effort by showin

Analysis of Instant Search Query Logs (Full Version)

Instant search is a new search paradigm that shows results as a user types in a query. It has become increasingly popular in recent years due to its simplicity and power. In an instant-search system, every keystroke from a user triggers a new request to the server. Therefore, its log has a richer content than that of a traditional search system, and previous log analysis research is not directly applicable to this type of log. In this paper, we study the problem of analyzing the query log of an instant-search system. We propose a classification scheme for user typing behaviors. We use the identified typing behaviors to estimate the success rate of such a system in the absence of click-through data. We also compare the log of an instant-search system and that of a traditional search system on the same data. The results show that on a people directory search system, instant search can typically save 2 seconds per search, reduce the typing effort by showing the results with fewer characters entered, and increase the success rate