This primer reviews the published literature on search result diversification. In particular, it discusses the motivations for diversifying the search results for an ambiguous query and provides a formal definition of the search result diversification problem. In addition, it describes the most successful approaches in the literature for producing and evaluating diversity in multiple search domains.
Provides an understanding of Web search engines from the unique perspective of Library and Information Science. This book explores a range of topics including retrieval effectiveness, user satisfaction, the evaluation of search interfaces, the impact of search on society, and the influence of search engine optimization (SEO) on results quality.
Evaluation has always played a major role in information retrieval, with the early pioneers such as Cyril Cleverdon and Gerard Salton laying the foundations for most of the evaluation methodologies in use today. The retrieval community has been extremely fortunate to have such a well-grounded evaluation paradigm during a period when most of the human language technologies were just developing. This lecture has the goal of explaining where these evaluation methodologies came from and how they have continued to adapt to the vastly changed environment in the search engine world today. The lecture starts with a discussion of the early evaluation of information retrieval systems, starting with the Cranfield testing in the early 1960s, continuing with the Lancaster "user" study for MEDLARS, and presenting the various test collection investigations by the SMART project and by groups in Britain. The emphasis in this chapter is on the how and the why of the various methodologies developed. The second chapter covers the more recent "batch" evaluations, examining the methodologies used in the various open evaluation campaigns such as TREC, NTCIR (emphasis on Asian languages), CLEF (emphasis on European languages), INEX (emphasis on semi-structured data), etc. Here again the focus is on the how and why, and in particular on the evolving of the older evaluation methodologies to handle new information access techniques. This includes how the test collection techniques were modified and how the metrics were changed to better reflect operational environments. The final chapters look at evaluation issues in user studies -- the interactive part of information retrieval, including a look at the search log studies mainly done by the commercial search engines. Here the goal is to show, via case studies, how the high-level issues of experimental design affect the final evaluations. Table of Contents: Introduction and Early History / "Batch" Evaluation Since 1992 / Interactive Evaluation / Conclusion
Portfolio Diversification provides an update on the practice of combining several risky investments in a portfolio with the goal of reducing the portfolio's overall risk. In this book, readers will find a comprehensive introduction and analysis of various dimensions of portfolio diversification (assets, maturities, industries, countries, etc.), along with time diversification strategies (long term vs. short term diversification) and diversification using other risk measures than variance. Several tools to quantify and implement optimal diversification are discussed and illustrated. - Focuses on portfolio diversification across all its dimensions - Includes recent empirical material that was created and developed specifically for this book - Provides several tools to quantify and implement optimal diversification
This monograph provides a comprehensible introduction to DPPs, focusing on the intuitions, algorithms, and extensions that are most relevant to the machine learning community.
In information retrieval, query auto completion (QAC), also known as type-ahead and auto-complete suggestion, helps users to formulate their query when they have an intent in mind but not a clear way of expressing this in a query. This monograph surveys this research.
This book constitutes the refereed proceedings of the 13th International Conference on Similarity Search and Applications, SISAP 2020, held in Copenhagen, Denmark, in September/October 2020. The conference was held virtually due to the COVID-19 pandemic. The 19 full papers presented together with 12 short and 2 doctoral symposium papers were carefully reviewed and selected from 50 submissions. The papers are organized in topical sections named: scalable similarity search; similarity measures, search, and indexing; high-dimensional data and intrinsic dimensionality; clustering; artificial intelligence and similarity; demo and position papers; and doctoral symposium.
International trade in 2009 is projected to contract for the first time since 1982. As a result, export diversifi cation has gained new urgency as one way of using exports to recover lost growth momentum. Moreover, diversifi cation is central to reducing income volatility and sustaining high growth rates, which are especially important for countries with large populations living in poverty. In the 1950s, countries became concerned that their dependence on primary products would lead to steady falls in the purchasing power of primary exports and thus slow growth. A major policy objective of developing countries since that time has been to diversify out of primary products into manufactures. Although some nations have been at least partially successful, many low-income countries remain dependent on a narrow range of primary products. 'Breaking Into New Markets' argues for a comprehensive view of diversifi cation. It explores new thinking and evidence about export diversifi cation and elaborates on policies for its promotion. These policies span tariffs and taxes, services, and government activities to help fi rms take advantage of global opportunities. The book is a compilation of chapters written as short, policy-focused pieces. Many digest longer, more academic papers in an effort to make the information accessible to a larger policy and nontechnical audience. In that sense, the book is a policy primer on what export diversifi cation can and cannot do for growth and how to make diversifi cation happen. Intelligently designed policies that effi ciently address the obstacles to export growth are critical for overall economic growth and poverty reduction. This book offers insights useful to policy makers and practitioners as they embark on efforts to design new programs of competitiveness in their trade strategies.
This book constitutes the refereed proceedings of the Third International Conference on the Theory of Information Retrieval, ICTIR 2011, held in Bertinoro, Italy, in September 2011. The 25 revised full papers and 13 short papers presented together with the abstracts of two invited talks were carefully reviewed and selected from 65 submissions. The papers cover topics ranging from query expansion, co-occurence analysis, user and interactive modelling, system performance prediction and comparison, and probabilistic approaches for ranking and modelling IR to topics related to interdisciplinary approaches or applications. They are organized into the following topical sections: predicting query performance; latent semantic analysis and word co-occurrence analysis; query expansion and re-ranking; comparison of information retrieval systems and approximate search; probability ranking principle and alternatives; interdisciplinary approaches; user and relevance; result diversification and query disambiguation; and logical operators and descriptive approaches.
