This book constitutes the proceedings of the 22nd International Conference on Theory and Practice of Digital Libraries, TPDL 2018, held in Porto, Portugal, in September 2018. The 51 full papers, 17 short papers, and 13 poster and tutorial papers presented in this volume were carefully reviewed and selected from 81 submissions. The general theme of TPDL 2018 was Digital Libraries for Open Knowledge. The papers present a wide range of the following topics: Metadata, Entity Disambiguation, Data Management, Scholarly Communication, Digital Humanities, User Interaction, Resources, Information Extraction, Information Retrieval, Recommendation.

This book constitutes the refereed proceedings of the 19th International Conference on Asia-Pacific Digital Libraries, ICADL 2017, held in Bangkok, Thailand, in November 2017. The 21 full papers and 6 short papers presented in this book were carefully reviewed and selected from 51 submissions. The paper topics of ICADL 2017 covered a wide spectrum from various areas, including information visualization, data mining/extraction, cultural heritage preservation, personalized service and user modeling, novel library content and use environments, electronic publishing, preservation systems and algorithms, social networking and information systems, Internet of things, cloud computing and applications, mobile services, interoperability issues, open source tools and systems, security and privacy, multi-language support, metadata and cataloguing, search, retrieval and browsing interfaces to all forms of digital content, e-Science/e-Research data and knowledge management, and cooperative service and community service.

This book offers a helpful starting point in the scattered, rich, and complex body of literature on Mobile Information Retrieval (Mobile IR), reviewing more than 200 papers in nine chapters. Highlighting the most interesting and influential contributions that have appeared in recent years, it particularly focuses on both user interaction and techniques for the perception and use of context, which, taken together, shape much of today's research on Mobile IR. The book starts by addressing the differences between IR and Mobile IR, while also reviewing the foundations of Mobile IR research. It then examines the different kinds of documents, users, and information needs that can be found in Mobile IR, and which set it apart from standard IR. Next, it discusses the two important issues of user interfaces and context-awareness. In closing, it covers issues related to the evaluation of Mobile IR applications. Overall, the book offers a valuable tool, helping new and veteran researchers alike to navigate this exciting and highly dynamic area of research.

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 13th International Conference on Asia-Pacific Digital Libraries, ICADL 2011, held in Beijing, China, in October 2011. The 33 revised full papers, 8 short papers and 9 poster papers presented were carefully reviewed and selected from 136 submissions. The topics covered are digital archives and preservation; information mining and extraction; medata, catalogue; distributed repositories and cloud computing; social network and personalized service; mobile services and electronic publishing; multimedia digital libraries; information retrieval; and tools and systems for digital library.

Information retrieval (IR) aims at defining systems able to provide a fast and effective content-based access to a large amount of stored information. The aim of an IR system is to estimate the relevance of documents to users' information needs, expressed by means of a query. This is a very difficult and complex task, since it is pervaded with imprecision and uncertainty. Most of the existing IR systems offer a very simple model of IR, which privileges efficiency at the expense of effectiveness. A promising direction to increase the effectiveness of IR is to model the concept of "partially intrinsic" in the IR process and to make the systems adaptive, i.e. able to "learn" the user's concept of relevance. To this aim, the application of soft computing techniques can be of help to obtain greater flexibility in IR systems.

This book constitutes the refereed proceedings of the 13th International Conference on String Processing and Information Retrieval, SPIRE 2006. The 26 revised full papers and 5 revised short papers presented together with 2 invited talks were carefully reviewed and selected. The papers are organized in topical sections on Web clustering and text categorisation, strings, user behaviour, Web search algorithms, compression, correction, information retrieval applications, bio-informatics, and Web search engines.

This book presents some recent works on the application of Soft Computing techniques in information access on the World Wide Web. The book comprises 15 chapters from internationally known researchers and is divided in four parts reflecting the areas of research of the presented works such as Document Classification, Semantic Web, Web Information Retrieval and Web Applications. This book demonstrates that Web Information Retrieval is a stimulating area of research where Soft Computing technologies can be applied satisfactorily.

CoLIS 5 was the ?fth in the series of international conferences whose general aim is to provide a broad forum for critically exploring and analyzing research inareassuchascomputerscience, informationscienceandlibraryscience.CoLIS examinesthehistorical, theoretical, empiricalandtechnicalissuesrelatingtoour understanding and use of information, promoting an interdisciplinary approach to research. CoLIS seeks to provide a broad platform for the examination of context as it relates to our theoretical, empirical and technical development of information-centered disciplines. The theme for CoLIS 5 was the nature, impact and role of context within information-centered research. Context is a complex, dynamic and multi- - mensional concept that in?uences both humans and machines: how they behave individually and how they interact with each other. In CoLIS 5 we took an interdisciplinary approach to the issue of context to help us understand and the theoretical approaches to modelling and understanding context, incorporate contextual reasoning within technology, and develop a shared framework for promoting the exploration of conte

The ongoing migration of computing and information access from the desktop and te- phone to mobile computing devices such as PDAs, tablet PCs, and next-generation (3G) phones poses critical challenges for research on information access. Desktop computer users are now used to accessing vast quantities of complex data either directly on their PC or via the Internet - with many services now blurring that distinction. The current state-of-practice of mobile computing devices, be they mobile phones, hand-held computers, or personal digital assistants (PDAs), is very variable. Most mobile phones have no or very limited information storage and very poor Internet access. Furthermore, very few end-users make any, never mind extensive, use of the services that are provided. Hand-held computers, on the other hand, tend to have no wireless network capabilities and tend to be used very much as electronic diaries, with users tending not to go beyond basic diary applications.

During recent years, huge efforts have been made to establish digital libraries, in a variety of media, offered from a variety of sources, and intended for a variety of professional and private user communities. As digital data collections proliferate, problems of resource selection and data fusion become major issues. Traditional search engines, even the best ones, are unable to provide access to the hidden web of information that is only available via digital library search interfaces.

Originating from the SIGIR 2003 Workshop on Distributed Information Retrieval, held in Toronto, Canada in August 2003, this book presents extended and revised workshop papers as well as several invited papers on the topic to round off coverage of the core issues. The papers are devoted to recent research on the design and implementation of methods and tools for resource discovery, resource description, resource selection, data fusion, and user interaction.

This book constitutes the refereed proceedings of the 24th European Colloquium on Information Retrieval Research, ECIR 2002, held in Glasgow, UK, in March 2002.The 23 revised full papers presented were carefully reviewed and selected from a total of 52 submissions. The papers are organized in topical sections on multimedia, Web-information retrieval, query modification, soft computing, models, categorization, structured documents, cross-language issues, and interactive systems.

Information Retrieval (IR) is concerned with the effective and efficient retrieval of information based on its semantic content. The central problem in IR is the quest to find the set of relevant documents, among a large collection containing the information sought, satisfying a user's information need usually expressed in a natural language query. Documents may be objects or items in any medium: text, image, audio, or indeed a mixture of all three. This book presents 12 revised lectures given at the Third European Summer School in Information Retrieval, ESSIR 2000, held at the Villa Monastero, Varenna, Italy, in September 2000. The first part of the book is devoted to the foundation of IR and related areas; the second part on advanced topics addresses various current issues, from usability aspects to Web searching and browsing.

Information retrieval (IR) aims at defining systems able to provide a fast and effective content-based access to a large amount of stored information. The aim of an IR system is to estimate the relevance of documents to users' information needs, expressed by means of a query. This is a very difficult and complex task, since it is pervaded with imprecision and uncertainty. Most of the existing IR systems offer a very simple model of IR, which privileges efficiency at the expense of effectiveness. A promising direction to increase the effectiveness of IR is to model the concept of "partially intrinsic" in the IR process and to make the systems adaptive, i.e. able to "learn" the user's concept of relevance. To this aim, the application of soft computing techniques can be of help to obtain greater flexibility in IR 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.

eRisk stands for Early Risk Prediction on the Internet. It is concerned with the exploration of techniques for the early detection of mental health disorders which manifest in the way people write and communicate on the internet, in particular in user generated content (e.g. Facebook, Twitter, or other social media). Early detection technologies can be employed in several different areas but particularly in those related to health and safety. For instance, early alerts could be sent when the writing of a teenager starts showing increasing signs of depression, or when a social media user starts showing suicidal inclinations, or again when a potential offender starts publishing antisocial threats on a blog, forum or social network. eRisk has been the pioneer of a new interdisciplinary area of research that is potentially applicable to a wide variety of situations, problems and personal profiles. This book presents the best results of the first five years of the eRisk project which started in 2017 and developed into one of the most successful track of CLEF, the Conference and Lab of the Evaluation Forum.

This book constitutes the refereed proceedings of the 10th International Conference of the CLEF Association, CLEF 2019, held in Lugano, Switzerland, in September 2019.The conference has a clear focus on experimental information retrieval with special attention to the challenges of multimodality, multilinguality, and interactive search ranging from unstructured to semi structures and structured data. The 7 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 30 submissions. This year, many contributions tackle the social networks with the detection of stances or early identification of depression signs on Twitter in a cross-lingual context. Further this volume presents 7 "best of the labs" papers which were reviewed as a full paper submission with the same review criteria. The labs represented scientific challenges based on new data sets and real world problems in multimodal and multilingual information access. In addition to this, 9 benchmarking labs reported results of their yearlong activities in overview talks and lab sessions.

This book constitutes the refereed proceedings of the 38th European Conference on IR Research, ECIR 2016, held in Padua, Italy, in March 2016. The 42 full papers and 28 poster papers presented together with 3 keynote talks and 6 demonstration papers, were carefully reviewed and selected from 284 submissions. The volume contains the outcome of 4 workshops as well as 4 tutorial papers in addition. Being the premier European forum for the presentation of new research results in the field of Information Retrieval, ECIR features a wide range of topics such as: social context and news, machine learning, question answering, ranking, evaluation methodology, probalistic modeling, evaluation issues, multimedia and collaborative filtering, and many more.