Using interaction data for improving the offline and online evaluation of search engines

This thesis investigates how web search evaluation can be improved using historical interaction data. Modern search engines combine offline and online evaluation approaches in a sequence of steps that a tested change needs to pass through to be accepted as an improvement and subsequently deployed. We refer to such a sequence of steps as an evaluation pipeline. In this thesis, we consider the evaluation pipeline to contain three sequential steps: an offline evaluation step, an online evaluation scheduling step, and an online evaluation step. In this thesis we show that historical user interaction data can aid in improving the accuracy or efficiency of each of the steps of the web search evaluation pipeline. As a result of these improvements, the overall efficiency of the entire evaluation pipeline is increased. Firstly, we investigate how user interaction data can be used to build accurate offline evaluation methods for query auto-completion mechanisms. We propose a family of offline evaluation metrics for query auto-completion that represents the effort the user has to spend in order to submit their query. The parameters of our proposed metrics are trained against a set of user interactions recorded in the search engine’s query logs. From our experimental study, we observe that our proposed metrics are significantly more correlated with an online user satisfaction indicator than the metrics proposed in the existing literature. Hence, fewer changes will pass the offline evaluation step to be rejected after the online evaluation step. As a result, this would allow us to achieve a higher efficiency of the entire evaluation pipeline. Secondly, we state the problem of the optimised scheduling of online experiments. We tackle this problem by considering a greedy scheduler that prioritises the evaluation queue according to the predicted likelihood of success of a particular experiment. This predictor is trained on a set of online experiments, and uses a diverse set of features to represent an online experiment. Our study demonstrates that a higher number of successful experiments per unit of time can be achieved by deploying such a scheduler on the second step of the evaluation pipeline. Consequently, we argue that the efficiency of the evaluation pipeline can be increased. Next, to improve the efficiency of the online evaluation step, we propose the Generalised Team Draft interleaving framework. Generalised Team Draft considers both the interleaving policy (how often a particular combination of results is shown) and click scoring (how important each click is) as parameters in a data-driven optimisation of the interleaving sensitivity. Further, Generalised Team Draft is applicable beyond domains with a list-based representation of results, i.e. in domains with a grid-based representation, such as image search. Our study using datasets of interleaving experiments performed both in document and image search domains demonstrates that Generalised Team Draft achieves the highest sensitivity. A higher sensitivity indicates that the interleaving experiments can be deployed for a shorter period of time or use a smaller sample of users. Importantly, Generalised Team Draft optimises the interleaving parameters w.r.t. historical interaction data recorded in the interleaving experiments. Finally, we propose to apply the sequential testing methods to reduce the mean deployment time for the interleaving experiments. We adapt two sequential tests for the interleaving experimentation. We demonstrate that one can achieve a significant decrease in experiment duration by using such sequential testing methods. The highest efficiency is achieved by the sequential tests that adjust their stopping thresholds using historical interaction data recorded in diagnostic experiments. Our further experimental study demonstrates that cumulative gains in the online experimentation efficiency can be achieved by combining the interleaving sensitivity optimisation approaches, including Generalised Team Draft, and the sequential testing approaches. Overall, the central contributions of this thesis are the proposed approaches to improve the accuracy or efficiency of the steps of the evaluation pipeline: the offline evaluation frameworks for the query auto-completion, an approach for the optimised scheduling of online experiments, a general framework for the efficient online interleaving evaluation, and a sequential testing approach for the online search evaluation. The experiments in this thesis are based on massive real-life datasets obtained from Yandex, a leading commercial search engine. These experiments demonstrate the potential of the proposed approaches to improve the efficiency of the evaluation pipeline.

Handle with care: historical geographies and difficult cultural legacies of egg-collecting

This thesis offers an examination of egg-collecting, which was a very popular pastime in Britain from the Victorian era well into the twentieth century. Collectors, both young and old, would often spend whole days and sometimes longer trips in a wide variety of different habitats, from sea shores to moorlands, wetlands to craggy mountainsides, searching for birds’ nests and the bounty to be found within them. Once collectors had found and taken eggs, they emptied out the contents; hence, they were really eggshell collectors. Some egg collectors claimed that egg-collecting was not just a hobby but a science, going by the name of oology, and seeking to establish oology as a recognised sub-discipline of ornithology, these collectors or oologists established formal institutions such as associations and societies, attended meetings where they exhibited unusual finds, and also contributed to specialist publications dedicated to oology. Egg-collecting was therefore many things at once: a culture of the British countryside, from where many eggs were taken; a culture of natural history, taking on the trappings of a science; and a culture of enthusiasm, providing a consuming passion for many collectors. By the early twentieth century, however, opposing voices were increasingly being raised, by conservation groups and other observers, about the impact that egg-collecting was having on bird populations and on the welfare of individual birds. By mid-century the tide had turned against the collectors, and egg-collecting in Britain was largely outlawed in 1954, with further restrictions imposed in 1981. While many egg collections have been lost or destroyed, some have been donated to museums, including Glasgow Museums (GM), which holds in its collections over 30,000 eggs. As a Collaborative Doctoral Award involving the University of Glasgow and GM, the project outlined in this thesis aims to bring to light and to life these egg collections, the activities of the collectors who originally built them, and the wider world of British egg-collecting. By researching archival material held by Glasgow Museums, published specialist egg-collecting journals and other published sources, as well as the eggs as a material archive, this thesis seeks to recover some of the practices and preoccupations of egg collectors. It also recounts the practical activities carried out during the course of the project at GM, particularly those involving a collection of eggs newly donated to the museum during the course of this project, culminating in a new temporary display of birds’ eggs at Glasgow Museums Resource Centre.