User engagement refers to the quality of the user experience that emphasizes the positive aspects of interacting with an online application and, in particular, the desire to use that application longer and repeatedly. User engagement is a key concept in the design of online applications (whether for desktop, tablet or mobile), motivated by the observation that successful applications are not just used, but are engaged with. Users invest time, attention, and emotion in their use of technology, and seek to satisfy pragmatic and hedonic needs. Measurement is critical for evaluating whether online applications are able to successfully engage users, and may inform the design of and use of applications. User engagement is a multifaceted, complex phenomenon; this gives rise to a number of potential measurement approaches. Common ways to evaluate user engagement include using self-report measures, e.g., questionnaires; observational methods, e.g. facial expression analysis, speech analysis; neuro-physiological signal processing methods, e.g., respiratory and cardiovascular accelerations and decelerations, muscle spasms; and web analytics, e.g., number of site visits, click depth. These methods represent various trade-offs in terms of the setting (laboratory versus ``in the wild''), object of measurement (user behaviour, affect or cognition) and scale of data collected. For instance, small-scale user studies are deep and rich, but limited in terms of generalizability, whereas large-scale web analytic studies are powerful but negate users' motivation and context. The focus of this book is how user engagement is currently being measured and various considerations for its measurement. Our goal is to leave readers with an appreciation of the various ways in which to measure user engagement, and their associated strengths and weaknesses. We emphasize the multifaceted nature of user engagement and the unique contextual constraints that come to bear upon attempts to measure engagement in different settings, and across different user groups and web domains. At the same time, this book advocates for the development of ``good'' measures and good measurement practices that will advance the study of user engagement and improve our understanding of this construct, which has become so vital in our wired world.

In recent years, there have been several attempts to define a logic for information retrieval (IR). The aim was to provide a rich and uniform representation of information and its semantics with the goal of improving retrieval effectiveness. The basis of a logical model for IR is the assumption that queries and documents can be represented effectively by logical formulae. To retrieve a document, an IR system has to infer the formula representing the query from the formula representing the document. This logical interpretation of query and document emphasizes that relevance in IR is an inference process. The use of logic to build IR models enables one to obtain models that are more general than earlier well-known IR models. Indeed, some logical models are able to represent within a uniform framework various features of IR systems such as hypermedia links, multimedia data, and user's knowledge. Logic also provides a common approach to the integration of IR systems with logical database systems. Finally, logic makes it possible to reason about an IR model and its properties. This latter possibility is becoming increasingly more important since conventional evaluation methods, although good indicators of the effectiveness of IR systems, often give results which cannot be predicted, or for that matter satisfactorily explained. However, logic by itself cannot fully model IR. The success or the failure of the inference of the query formula from the document formula is not enough to model relevance in IR. It is necessary to take into account the uncertainty inherent in such an inference process. In 1986, Van Rijsbergen proposed the uncertainty logical principle to model relevance as an uncertain inference process. When proposing the principle, Van Rijsbergen was not specific about which logic and which uncertainty theory to use. As a consequence, various logics and uncertainty theories have been proposed and investigated. The choice of an appropriate logic and uncertainty mechanism has been a main research theme in logical IR modeling leading to a number of logical IR models over the years. Information Retrieval: Uncertainty and Logics contains a collection of exciting papers proposing, developing and implementing logical IR models. This book is appropriate for use as a text for a graduate-level course on Information Retrieval or Database Systems, and as a reference for researchers and practitioners in industry.

This book constitutes the refereed proceedings of the Second International Conference on Multilingual and Multimodal Information Access Evaluation, in continuation of the popular CLEF campaigns and workshops that have run for the last decade, CLEF 2011, held in Amsterdem, The Netherlands, in September 2011.
The 14 revised full papers presented together with 2 keynote talks were carefully reviewed and selected from numerous submissions. The papers accepted for the conference included research on evaluation methods and settings, natural language processing within different domains and languages, multimedia and reflections on CLEF. Two keynote speakers highlighted important developments in the field of evaluation: the role of users in evaluation and a framework for the use of crowdsourcing experiments in the setting of retrieval evaluation."

Welcome to the proceedings of the 6th workshop of the Initiative for the Ev- uation of XML Retrieval (INEX) Now in its sixth year, INEX has become an established evaluation forum for XML information retrieval (IR), with over 100 participating organizations worldwide. Its aim is to provide an infrastructure, in the form of a large XML test collection and appropriate scoring methods, for the evaluation of XML IR systems. XMLIRis playinganincreasinglyimportantroleinmanyinformationaccess systems(e.g., digitallibraries, web, intranet)wherecontentisbecomingmoreand more a mixture of text, multimedia, and metadata, formatted according to the adopted W3C standard for information repositories, the so-called eXtensible MarkupLanguage(XML).Theultimategoalofsuchsystemsistoprovidetheright contenttotheirend-users.However, whilemanyoftoday'sinformationaccesss- temsstilltreatdocumentsassinglelarge(text)blocks, XMLo?erstheopportunity toexploittheinternalstructureofdocumentsinordertoallowformoreprecise- cess, thusprovidingmorespeci?canswerstouserrequests.Providinge?ective- cesstoXML-basedcontentisthereforeakeyissueforthesuccessofthesesystems. The aim of the INEX 2007 workshop was to bring together researchers in the ?eld of XML IR who participated in the INEX 2007 campaign. During the past year participating organizations contributed to the building of a large-scale XML test collection by creating topics, performing retrieval runs and providing relevance assessments. The workshop brought together the results of this lar- scale e?ort, summarized and addressed the issues encountered, and devised a work plan for the future evaluation of XML retrieval systems. In total sevenresearchtrackswereincluded in INEX 2007.Thesestudied d- ferentaspectsofXMLinformationaccess: ad-hoc, documentmining, multimedia, heterogeneous, entity ranking, book search, and link-the-wiki. The consolidation of the existing tracks, and the expansion to new areas o?ered by the new tracks has enabled INEX to extend its scope. This volume contains 37 papers selected from 50 submitted ones (74% acceptance rate). Each paper was peer-re

This book constitutes the thoroughly refereed post-proceedings of the 5th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2006, held at Dagstuhl Castle, Germany, in December 2006.

The 49 revised full papers presented were carefully selected for presentation at the workshop and went through a subsequent round of careful reviewing and revision. The papers are organized in topical sections on methodology, and 7 additional tracks on ad-hoc, natural language processing, heterogeneous collection, multimedia, interactive, use case, as well as document mining.

This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2005, held at Dagstuhl Castle, Germany, in November 2005. The book presents 41 revised full papers, organized in topical sections on methodology, multiple retrieval, ad-hoc retrieval, relevance feedback, natural language queries, and more heterogeneous retrieval, interactive retrieval, document mining, and multimedia retrieval.

This book constitutes the refereed proceedings of the 28th European Conference on Information Retrieval Research, ECIR 2006, held in London, April 2006. The 37 revised full papers and 28 revised poster papers presented are organized in topical sections on formal models, document and query representation and text understanding, topic identification and news retrieval, clustering and classification, refinement and feedback, performance and peer-to-peer networks, Web search, cross-language retrieval, genomic IR, and much more.

The ultimate goal of many information access systems (e.g., digital libraries, the Web, intranets) is to provide the right content to their end-users. This content is increasingly a mixture of text, multimedia, and metadata, and is formatted according to the adopted W3C standard for information repositories, the so-called eXtensible Markup L- guage (XML). Whereas many of today s information access systems still treat do- ments as single large (text) blocks, XML offers the opportunity to exploit the internal structure of documents in order to allow for more precise access thus providing more specific answers to user requests. Providing effective access to XML-based content is therefore a key issue for the success of these systems. The aim of the INEX campaign (Initiative for the Evaluation of XML Retrieval), which was set up at the beginning of 2002, is to establish infrastructures, XML test suites, and appropriate measurements for evaluating the performance of information retrieval systems that aim at giving effective access to XML content. More precisely, the goal of the INEX initiative is to provide means, in the form of a large XML test collection and appropriate scoring methods, for the evaluation of content-oriented XML retrieval systems."

In recent years, there have been several attempts to define a logic for information retrieval (IR). The aim was to provide a rich and uniform representation of information and its semantics with the goal of improving retrieval effectiveness. The basis of a logical model for IR is the assumption that queries and documents can be represented effectively by logical formulae. To retrieve a document, an IR system has to infer the formula representing the query from the formula representing the document. This logical interpretation of query and document emphasizes that relevance in IR is an inference process. The use of logic to build IR models enables one to obtain models that are more general than earlier well-known IR models. Indeed, some logical models are able to represent within a uniform framework various features of IR systems such as hypermedia links, multimedia data, and user's knowledge. Logic also provides a common approach to the integration of IR systems with logical database systems. Finally, logic makes it possible to reason about an IR model and its properties. This latter possibility is becoming increasingly more important since conventional evaluation methods, although good indicators of the effectiveness of IR systems, often give results which cannot be predicted, or for that matter satisfactorily explained. However, logic by itself cannot fully model IR. The success or the failure of the inference of the query formula from the document formula is not enough to model relevance in IR. It is necessary to take into account the uncertainty inherent in such an inference process. In 1986, Van Rijsbergen proposed the uncertainty logical principle to model relevance as an uncertain inference process. When proposing the principle, Van Rijsbergen was not specific about which logic and which uncertainty theory to use. As a consequence, various logics and uncertainty theories have been proposed and investigated. The choice of an appropriate logic and uncertainty mechanism has been a main research theme in logical IR modeling leading to a number of logical IR models over the years. Information Retrieval: Uncertainty and Logics contains a collection of exciting papers proposing, developing and implementing logical IR models. This book is appropriate for use as a text for a graduate-level course on Information Retrieval or Database Systems, and as a reference for researchers and practitioners in industry.