Bodo Billerbeck

Bodo Billerbeck, Justin Zobel, Nicholas Lester et al.

Search techniques make use of elementary information such as term frequencies and document lengths in computation of similarity weighting. They can also exploit richer statistics, in particular the number of documents in which any two terms co-occur. In this paper we propose alternative methods for computing this statistic, a challenging task because the number of distinct pairs of terms is vast -- around 100,000 in a typical 1000-word news article, for example. In contrast, we do not employ approximation algorithms, as we want to be able to find exact counts. We explore their efficiency, finding that a naïve approach based on a dictionary is indeed very slow, while methods based on a combination of inverted indexes and linear scanning provide both massive speed-ups and better observed asymptotic behaviour. Our careful implementation shows that, with our novel list-pairs approach it is possible to process over several hundred thousand documents per hour.

Nick Craswell, Daniel Campos, Bhaskar Mitra et al.

Users of Web search engines reveal their information needs through queries and clicks, making click logs a useful asset for information retrieval. However, click logs have not been publicly released for academic use, because they can be too revealing of personally or commercially sensitive information. This paper describes a click data release related to the TREC Deep Learning Track document corpus. After aggregation and filtering, including a k-anonymity requirement, we find 1.4 million of the TREC DL URLs have 18 million connections to 10 million distinct queries. Our dataset of these queries and connections to TREC documents is of similar size to proprietary datasets used in previous papers on query mining and ranking. We perform some preliminary experiments using the click data to augment the TREC DL training data, offering by comparison: 28x more queries, with 49x more connections to 4.4x more URLs in the corpus. We present a description of the dataset's generation process, characteristics, use in ranking and suggest other potential uses.