Operators for Similarity Search: Semantics, Techniques and Usage Scenarios

This book provides a comprehensive tutorial on similarity operators. The authors systematically survey the set of similarity operators, primarily focusing on their semantics, while also touching upon mechanisms for processing them effectively.

The book starts off by providing introductory material on similarity search systems, highlighting the central role of similarity operators in such systems. This is followed by a systematic categorized overview of the variety of similarity operators that have been proposed in literature over the last two decades, including advanced operators such as RkNN, Reverse k-Ranks, Skyline k-Groups and K-N-Match. Since indexing is a core technology in the practical implementation of similarity operators, various indexing mechanisms are summarized. Finally, current research challenges are outlined, so as to enable interested readers to identify potential directions for future investigations.

In summary, this book offers a comprehensive overview of the field of similarity search operators, allowing readers to understand the area of similarity operators as it stands today, and in addition providing them with the background needed to understand recent novel approaches.

Improving Recall of Regular Expressions for Information Extraction

Learning or writing regular expressions to identify instances of a specific
concept within text documents with a high precision and recall is challenging.
It is relatively easy to improve the precision of an initial regular expression
by identifying false positives covered and tweaking the expression to avoid the
false positives. However, modifying the expression to improve recall is difficult
since false negatives can only be identified by manually analyzing all documents,
in the absence of any tools to identify the missing instances. We focus on partially
automating the discovery of missing instances by soliciting minimal user
feedback. We present a technique to identify good generalizations of a regular
expression that have improved recall while retaining high precision. We empirically
demonstrate the effectiveness of the proposed technique as compared to
existing methods and show results for a variety of tasks such as identification of
dates, phone numbers, product names, and course numbers on real world datasets

Protocol for a pilot randomised controlled trial of an intervention to increase the use of traffic light food labelling in UK shoppers (the FLICC trial)

Background: Traffic light labelling of foods—a system that incorporates a colour-coded assessment of the level of total fat, saturated fat, sugar and salt on the front of packaged foods—has been recommended by the UK Government and is currently in use or being phased in by many UK manufacturers and retailers. This paper describes a protocol for a pilot randomised controlled trial of an intervention designed to increase the use of traffic light labelling during real-life food purchase decisions.

Methods/design: The objectives of this two-arm randomised controlled pilot trial are to assess recruitment, retention and data completion rates, to generate potential effect size estimates to inform sample size calculations for the main trial and to assess the feasibility of conducting such a trial. Participants will be recruited by email from a loyalty card database of a UK supermarket chain. Eligible participants will be over 18 and regular shoppers who frequently purchase ready meals or pizzas. The intervention is informed by a review of previous interventions encouraging the use of nutrition labelling and the broader behaviour change literature. It is designed to impact on mechanisms affecting belief and behavioural intention formation as well as those associated with planning and goal setting and the adoption and maintenance of the behaviour of interest, namely traffic light label use during purchases of ready meals and pizzas. Data will be collected using electronic sales data via supermarket loyalty cards and web-based questionnaires and will be used to estimate the effect of the intervention on the nutrition profile of purchased ready meals and pizzas and the behavioural mechanisms associated with label use. Data collection will take place over 48 weeks. A process evaluation including semi-structured interviews and web analytics will be conducted to assess feasibility of a full trial.

Discussion: The design of the pilot trial allows for efficient recruitment and data collection. The intervention could be generalised to a wider population if shown to be feasible in the main trial.