Web retrieval, ranking and personalization

Humans have used electronic information retrieval (IR) systems for more than 50 years as they evolved from experimental systems to full-scale Web search engines and digital libraries. The fields of library and information science (LIS), cognitive science, human factors and computer science have historically been the leading disciplines in conducting research that seeks to model human interaction with IR systems for all kinds of information related behaviors. As technology problems have been mastered, the theoretical and applied framework for studying human interaction with IR systems has evolved from systems-centered to more user-centered, or cognitive-centered approaches. However, cognitive information retrieval (CIR) research that focuses on user interaction with IR systems is still largely under-funded and is often not included at computing and systems design oriented conferences. But CIR-focused research continues, and there are signs that some IR systems designers in academia and the Web search business are realizing that user behavior research can provide valuable insights into systems design and evaluation. The goal of our book is to provide an overview of new CIR research directions. This book does not provide a history of the research field of CIR. Instead, the book confronts new ways of looking at the human information condition with regard to our increasing need to interact with IR systems. The need has grown due to a number of factors, including the increased importance of information to more people in this information age. Also, IR was once considered document-oriented, but has now evolved to include multimedia, text, and other information objects. As a result, IR systems and their complexity have proliferated as users and user purposes for using them have also proliferated. Human interaction with IR systems can often be frustrating as people often lack an understanding of IR system functionality. New more holistic directions in CIR are emerging that conceptualize human-IR system interaction at the human-computer interaction level (taking into account interface issues), the information behavior level (taking into account the role of IR system interaction in the total range of people’s information behaviors), and the

The study of cross-lingual Information Retrieval Systems (IRSs) and a deep analysis of system performances should provide guidelines, hints, and directions to drive the design and development of the next generation MultiLingual Information Access (MLIA) systems. In addition, effective tools for interpreting and comparing the experimental results should be made easily available to the research community. To this end, we propose a twofold methodology for the evaluation of Cross Language Information Retrieval (CLIR) systems: statistical analyses to provide MLIA researchers with quantitative and more sophisticated analysis techniques; and graphical tools to allow for a more qualitative comparison and an easier presentation of the results. We provide concrete examples about how the proposed methodology can be applied by studying the monolingual and bilingual tasks of the Cross-Language Evaluation Forum (CLEF) 2005 and 2006 campaigns.KeywordsInformation RetrievalMean Average PrecisionGraphical ToolBilingual ComparisonBilingual PerformanceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Providing educational services to students with disabilities requires a unique combination of professional knowledge, and adherence to complex compliance and auditing goals. This study investigates the information access gaps within special education health services. Through think-aloud activities with therapy supervisors, practitioners, and administrative staff, we elicited explicit and implicit information needs, and identified significant challenges in current information seeking and documentation practices in this highly regulated environment. Thematic analysis of 329 coded segments (including 120 task descriptions, 123 pain points, and 86 desired features) reveals systematic mismatches between information capture and retrieval practices, which practitioners navigate daily, highlighting a necessity for information seeking beyond traditional search and demonstrating use cases for AI-augmented information retrieval. We present design implications, developed in collaboration with these stakeholders, focused on enhancing task documentation and designing interaction to support these needs, offering a roadmap for future information interaction systems in this complex, multi-stakeholder domain.

This chapter provides a perspective on a problem-based learning (PBL) approach to teaching information retrieval (IR) theory, techniques, and practice at under- and postgraduate levels. The educational philosophy of PBL is outlined, and its pertinence to addressing the challenges of teaching IR in terms of both the diverse nature of the subject and also of the students is discussed. It is argued that teaching IR as a solution to a problem (access to information) and as a problem (how can we organize information in IR systems so it can be accessed) provides an engaging and challenging way to teach it to a range of students. It also draws connections between IR theory and techniques and relates IR to other disciplines through showing how similar problems are faced in other subjects. Some specific examples of teaching exercises based on PBL are provided with a discussion and reflection on their effectiveness. Finally assessment and feedback from students are discussed.

Information Retrieval (IR) systems aim to retrieve data that satisfies certain requirements and constitute an important service in many types of networks, including Delay/Disruption Tolerant Networks (DTNs). In current DTN based IR systems, the data that satisfies a query is assumed to be stored on a single node. Therefore, once a node receives a query in which it has the corresponding data, the query can be resolved completely. However, in scenarios where a query requires data from multiple nodes, these IR systems may fail. Henceforth, in this paper, we propose Distributed Data-Centric Information Retrieval (DDC-IR), a data centric IR system that supports all query types; e.g., continuous and complex. More importantly, it is designed specifically to operate in DTNs. It also incorporates a new packet, aka Query Reply Packet, that includes both a query and one or more replies. We show how this packet facilitates efficient query resolution and enables data centric routing. In addition, it uses caching so that nodes store popular queries that has the effect of speeding up query resolution. We have conducted an extensive simulation study to compare DDC-IR to state of the art IR systems using the popular Random Waypoint model and a trace-file containing student movements on a campus. The results show that DDC-IR is able to resolve 50 % more queries and has an 80 % lower buffer occupancy level than existing IR systems. We also tested DDC-IR in networks with varying sizes. For networks with 100 nodes, DDC-IR is able to resolve queries while current IR systems fail to resolve any queries. In particular, when the number of nodes increases, current IR systems fail to resolve any queries, whilst DDC-IR is able to resolve complex and continuous queries. The influence of the number of sub-queries on query resolution time is also studied. Specifically, when the number of sub-queries in a complex query increases from five to nine, DDC-IR uses 50 % more time to resolve a query. In comparison, prior IR systems fail to resolve any queries.

Purpose – People often engage in different information-seeking strategies (ISSs) within a single information-seeking episode. A critical concern for the design of information retrieval (IR) systems is how to provide support for these different behaviors in a manner which searchers can easily understand, navigate and use, as they move from one ISS to another. The purpose of this paper is to describe a dialogue structure that was implemented in an experimental IR system, in order to address this concern. Design/methodology/approach – The authors conducted a user-centered experiment to evaluate the IR systems. Participants were asked to search for information on two different task types, with four different topics per task, in both the experimental system and a baseline system emulating state-of-the-art IR systems. The authors report here the results related explicitly to the use of the experimental system's dialogue structure. Findings – For one of the task types, most participants followed the search steps as predicted in the dialogue structures, and those who did so completed the task in fewer moves. For the other task type, predicted order of moves was often not followed, but participants again used fewer moves when following the predicted order. Results demonstrate that the dialogue structures the authors designed indeed support effective human information behavior patterns in a variety of ways, and that searchers can effectively use a system which changes to support different ISSs. Originality/value – This study shows that it is both possible and beneficial, to design an IR system which can support multiple ISSs, and that such a system can be understood and used successfully.

This paper presents an outline of models of information seeking and other aspects of information behaviour, showing the relationship between communication and information behaviour in general with information seeking and information searching in information retrieval systems. It is suggested that these models address issues at various levels of information behaviour and that they can be related by envisaging a ‘nesting’ of models. It is also suggested that, within both information seeking research and information searching research, alternative models address similar issues in related ways and that the models are complementary rather than conflicting. Finally, an alternative, problem‐solving model is presented, which, it is suggested, provides a basis for relating the models in appropriate research strategies.

This minitrack addresses a broad range of issues related to the design of the next generation of information retrieval systems, especially related to improving web search effectiveness from the user perspective. The core of this research is how to help the user access and make use of digital data. These issues are of prime interest to researchers, developers, and information managers. The multidisciplinary nature of this emerging area allows us to engage as a community of participants with a wide range of interests, including retrieval design, HCI, information seeking behavior, and information management. Information Retrieval supports the computerized search of large document and digital media collections (millions or billions of items) to select small subsets of those documents relevant to a user's information need. Such algorithms are the basis for internet search engines and question-answering systems. At the same time, we know relatively little about the users who deal with a multi-billion-page Web. Further research is needed to address the user issues related to effectiveness and quality of experience when interacting with search engines. New metrics and methodologies are needed for retrieval evaluation as both the data sets of interest and user expectations grow exponentially. A focus on the user perspective allows us to align the user focus and the system focus in a multi-disciplinary forum that includes theoretical foundations, evaluation measures, methodologies, case studies and user study results. This year in the Information Access & Retrieval MiniTrack we include papers that cover this multidisciplinary approach. One paper, Appropriate Software Components for Mobile End-User Devices Executive Information Systems Up Close and Personalized as an Example, presents design principles for the design of interfaces for mobile devices. Two papers, Building Support for Web Information Gathering Tasks, and Characterizing Queries in Different Search Tasks, explore user behavior related to web search. The first paper examines characteristics of search specific to longer gathering tasks. The second of these papers explores the more general issue of types of tasks for a range of web information needs. The paper, Determinants of Information Channel Choice: The Impact of Task Complexity and Dispositional Character Traits, is a behavioral study of how made channel choice. The final paper, Cobre: A Comparative Book Reader for Los Primeros Libros, presents a novel reader model based on film strip metaphor. 2012 45th Hawaii International Conference on System Sciences

Information retrieval has taken an important turn when the researchers started using user behavior to improve their ranking algorithms. With the advent of user behavior in information retrieval, the interactive information retrieval is beginning to make its mark. In this paper, we discuss how user behavior is being used in information retrieval. We survey various strategies used for incorporating user behavior into information retrieval. The key fact is that taking absolute feedback about whether the retrieved documents are relevant or not is very difficult, and if we can take the implicit feedback from the user in the form of user behavior, we can arrive at a better learning function for the algorithm. We, in this paper, would like to provide a case study of various approaches in using user behavior for information retrieval.

In this paper discussed about information seeking behavior of library users of the State University of Padang Postgraduate Library because of a lack of knowledge in finding the information they need precisely and quickly. Because not a few postgraduate users who feel confused in finding the information needed. This research question covers how post-market visitors' information seeking behavior encompasses the stages of their activities. The purpose of writing this paper is to describe the behavior of information retrieval of postgraduate library students at Padang State University. The method of data collection is carried out on librarians and librarians through observation, interviews, and library studies in the Postgraduate Library of Padang State University. Analyzing data is done descriptively.Based on analyzing the data, it was concluded that in searching for library information in the Postgraduate Library of Padang State University there are two stages, namely: (1) behavior of the user when searching for information with the user strategy in information retrieval, which includes: starting, browsing, and extracting, (2) meanwhile, the technique of searching information on librarians in the Postgraduate Library of Padang State University shows that in conducting information search, library users use information search techniques based on words and information search techniques based on the closest words.Keywords: optimization, competence, electronic archives.

F. Wilfrid Lancaster has earned a reputation for greatness in the evaluation of information storage and retrieval systems. Many of his extensive contributions stem from his early experience with the National Library of Medicine (NLM) MEDLARS system. His evaluation of the MEDLARS Demand Search Service in 1966 and 1967 was an important landmark as one of the earliest evaluations of a computer-based retrieval system and as the first application of re-call and precision measures in a large, operational database setting. In 1971, his evaluation of the MEDLARS AIM-TWX system was an important study of early online systems and their direct use by end users. This paper summarizes Lancaster’s two major evaluations of the MEDLARS system, including the information environment at the time and their impact in the field of information science. Examples of Lancaster’s other evaluation work with information retrieval systems are provided, followed by discussion of the textbooks that grew out of his evaluation experience and expertise. The article closes with comments from current and former NLM staff regarding Lancaster’s time at NLM or his influence on their own career.

It is our great pleasure to welcome you to New Brunswick, New Jersey and the third ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2018). CHIIR, as you may know, has roots in two previously successful communities: The Information Interaction in Context (IIiX) conference and the Human Computer Information Retrieval (HCIR) symposium, which ran from 2006 and 2007 respectively. These meetings were focused on issues that involved Human Information Behavior (HIB), Interactive Information Retrieval (IIR) and Human-Computer Interaction (HCI). Those roots, as well as decades of research and development on information seeking and other forms of information interaction, human-centered design, and information retrieval are the backbone of CHIIR. At the same time, this vibrant new community has picked up more scholars and themes as it continues to attract new students and professionals, as well as emerging research topics that are evident in this year's program. In fact, CHIIR is one of the few forums that explicitly supports presentation of bold new ideas through its Perspective Papers category. In addition, we have picked up Demos as a new category for presentations this year. All of these wonderful things could not be possible without a large number of people making significant contributions. We are quite fortunate to have Katriina Byström, Falk Scholer, and Jeff Huang as our Program Chairs this year. These three brave souls took upon a tremendous effort of working with dozens of submissions, reviewers, and meta-reviewers and constructing a high-quality program while coordinating from three different continents. Soo Young Rieh and Preben Hansen, on the other hand dealt with higher than expected load for short papers and still managed to get them reviewed and assessed on time. Even our Doctoral Consortium (DC) this year ended up being quite challenging as we received twice as many submissions as before, but our fine DC chairs Jaceck Gwizdka and Vivek Singh found world-class mentors for these doctoral students. Thanks to our Workshops and Tutorials Chair Xiaojun Yuan, we have a fantastic lineup of tutorials on the first day and workshops on the last day. When the whole program was ready for the conference, it was our Proceedings Chair Roberto Gonzalez-Ibanez who managed to put together these proceedings that you are holding in your hands, or more likely viewing in the ACM Digital Library! We are thankful for having an energetic and resourceful local arrangement committee with Michael Cole as the Treasurer, Fernando Diaz as the Sponsorship Chair, Kaitlin Costello as the Local Organizing Chair, and Sunyoung Kim and Matt Mitsui as the Student Volunteers Chairs. And it was our Publicity Chair Anita Crescenzi, who helped us with not only the outreach efforts, but also with the registration system. Finally, none of these would have happened without the authors and reviewers from more than 30 countries whose contributions are reflected in every aspect of this conference. So, thank you all!

In modern information retrieval (IR) systems, scoring functions have been extensively adopted for sorting results. For a given document, the rank in sorted result lists with respect to hot searches can be considered as its influence. When a new document comes, can we use such IR systems to evaluate its influence before we insert it into the corpus? Such issue may not be solved very well by current IR systems with inverted indexes. In this paper, an influence measure based on documents’ global rank is proposed, and the inverted index structure has been extended by adding the position milestones for speeding up the ranking calculation. Moreover, a performance study using both real data and synthetic data verifies the effectiveness and the efficiency of our method.

Document relevance has been the primary focus in the design, optimization and evaluation of retrieval systems. Traditional testcollections are constructed by asking judges the relevance grade for a document with respect to an input query. Recent work of Yilmaz et al. found an evidence that effort is another important factor in determining document utility, suggesting that more thought should be given into incorporating effort into information retrieval. However, that work did not ask judges to directly assess the level of effort required to consume a document or analyse how effort judgements relate to traditional relevance judgements. In this work, focusing on three aspects associated with effort, we show that it is possible to get judgements of effort from the assessors. We further show that given documents of the same relevance grade, effort needed to find the portion of the document relevant to the query is a significant factor in determining user satisfaction as well as user preference between these documents. Our results suggest that if the end goal is to build retrieval systems that optimize user satisfaction, effort should be included as an additional factor to relevance in building and evaluating retrieval systems. We further show that new retrieval features are needed if the goal is to build retrieval systems that jointly optimize relevance and effort and propose a set of such features. Finally, we focus on the evaluation of retrieval systems and show that incorporating effort into retrieval evaluation could lead to significant differences regarding the performance of retrieval systems.

Cel/teza: Celem artykułu jest przedstawienie koncepcji i zasad działania nawigacji fasetowej (kiero­wanej) i wyszukiwania fasetowego oraz ich zastosowania w katalogach bibliotecznych. Koncepcja/metody badań: Scharakteryzowano metodę organizowania dostępu do zasobów informacji za pomocą faset odpowiadających kryteriom wyszukiwania. Omówiono podstawowe cechy architektury informacji systemów wyszukiwania fasetowego oraz modele zachowań informacyjnych użytkowników, na podstawie których takie systemy są budowane. Analizie porównawczej poddano zastosowanie wyszukiwania fasetowego w katalogach komputerowych na przykładzie katalogów elektronicznych (OPAC) pięciu bibliotek narodowych: Biblioteki Brytyjskiej (British Library), Biblioteki Kongresu (Li­brary of Congress), Biblioteki Narodowej Walii (Llyfrgell Genedlaethol Cymru – National Library of Wales), Biblioteki Narodowej Australii (National Library of Australia) i Rosyjskiej Biblioteki Narodowej (Rossijskoj Nacionalnoj Biblioteki). Dane do analizy zbierane były od czerwca do września 2014 r. Wyniki i wnioski: Rozwój technologii informacyjnej doprowadził do odrodzenia koncepcji S. R. Ran­ganathana wieloaspektowego systemu klasyfikacji treści, ułatwiającego odszukanie informacji wieloma drogami. Klasyfikacja fasetowa jest dziś jedną z najczęściej stosowanych metod organizowania treści w serwisach internetowych o charakterze komercyjnym, choć większość autorów systemów katego­ryzacji treści, które oparte są na tej klasyfikacji nie zdaje sobie z tego sprawy. Zastosowanie faset do zawężania rezultatów wyszukiwania jest już standardem w komercyjnych serwisach internetowych, w systemach bibliotecznych zaś innowacja ta nie jest jeszcze powszechna. Nie ma przyjętych czy zalecanych wzorców. W badanych katalogach zauważono różnice w liczbie kategorii oferowanych użytkownikom w interfejsach wyszukiwania fasetowego oraz ich nazewnictwie. Oryginalność/wartość poznawcza: Tematyka wykorzystania faset i klasyfikacji fasetowej w mechani­zmach wyszukiwania jest w Polsce rzadko poruszana. Autorowi nie są znane badania nad wykorzystaniem tego typu mechanizmu w serwisach internetowych związanych z działalnością informacyjno-biblioteczną.