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Jigs and Lures: Associating Web Queries with Structured Entities

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Academic year: 2020

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Figure

Figure 1: Example Q E Cgraph: (a) Sample queries in Q , clicks connecting queries with urls in U , and clicks toentities in E ; (b) Zoom on edges in Cu illustrating clicks observed on urls with weight wu( q , u  ) as well as synonymyedges between queries with similarity score s ( q i , q j ) (Section 3.2); (c) Zoom on edges in Ce where solid lines indicateobserved clicks with weight we( q , e  ) and dotted lines indicate inferred clicks with smoothed weightw ˆe( q , e  ) (Sec-tion 3.3); and (d) A temporal sequence of queries in a search session illustrating entity associations propagating fromthe Q E Cgraph to the queries in the session (Section 4).
Table 1: Models for estimating the association probabil-ity P( e | q ) .
Figure 2: Alpha tuning on held out data.
Figure 3: MSE of each model against the number ofclicks in the TEST corpus. Buckets scaled by query in-stance coverage of all queries with 10 or fewer clicks.
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