Rethinking Interest in Studies of Interactive Information Retrieval

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!

This paper presents an iterative and interactive information retrieval (IR) system for Web search using formal concept analysis (FCA). FCA provides a natural way to organise objects according to their properties and it has been used in recent work to organise search engine results. The navigation over the lattice helps the user to explore a structured and synthetic result. Such a lattice contains concepts that are relevant and others that are not relevant regarding a given IR task. In this way, lattices are introduced in an interactive and iterative system. The user expresses his negative or positive agreement with some concept of the lattice in respect of his objective of IR. These user choices are converted into operations over the lattice. The lattice is dynamically updated for a better fit to the request.

Since Information Retrieval (IR) is an interactive process in general, it is important to study Interactive Information Retrieval (IIR), where we would attempt to model and optimize an entire interactive retrieval process (rather than a single query) with consideration of many different ways a user can potentially interact with a search engine. This tutorial systematically reviews the progress of research in IIR with an emphasis on the most recent progress in the development of models, algorithms, and evaluation strategies for IIR. It starts with a broad overview of research in IIR and then gives an introduction to formal models for IIR using a cooperative game framework and covering decision-theoretic models such as the Interface Card Model and Probability Ranking Principle for IIR. Next, it provides a review of some representative specific techniques and algorithms for IIR, such as various forms of feedback techniques and diversification of search results, followed by a discussion of how an IIR system should be evaluated and multiple strategies proposed recently for evaluating IIR using user simulation. The tutorial ends with a brief discussion of the major open challenges in IIR and some of the most promising future research directions.

Task complexity is a critical task characteristic that influences users' information seeking and search behavior. In general, researchers differentiate task complexity from objective and subjective task complexity. Both significantly affect task performance. However, few studies have been done to examine how task complexity could be measured from users' perspective in information science. The present study identifies a set of objective and subjective measures and conducted a survey. The survey asked users to judge the complexity of a task, and then give the reasons why they made that judgment based on the measures. Six simulated task situations were developed for the survey and 168 valid questionnaires (84% return rate) were analyzed. The results indicate that the number of words hard to understand, the number of languages required for search results, and the number of domain areas involved in a task could significantly predict task complexity. The study helps further understand the attributes of task complexity and has implications in research on interactive information retrieval (IIR), task‐based information seeking and search, and personalization of information retrieval (IR).

Toward Cranfield-inspired reusability assessment in interactive information retrieval evaluation

Traditional information retrieval algorithms ignore user needs and are unable to obtain user gaze coordinates and gaze times, resulting in low retrieval accuracy. The author proposes a new interactive information retrieval algorithm for this purpose. Divide eye tracking technology evaluation indicators, visually process eye movement information, obtain user gaze coordinates and gaze time, and calculate the influence coefficients of each gaze area and each point in the area. Weighted visual words are accumulated to get a visual word list with the weight of the associated area, and visual word list and Rocchio algorithm are combined to build a hidden Relevance feedback retrieval model in semantic space to judge information retrieval preferences. Intelligent robot is introduced, and Jensen Shannon divergence is used to calculate the Kullback–Leibler divergence distance between the probability distributions of document sets, calculate the similarity matching, and complete the interactive information retrieval. The simulation results prove that, due to the introduction of intelligent robot strategy in this method, the amount of irrelevant retrieval information is reduced by matching user needs and retrieval results. Therefore, the amount of messages generated by information retrieval is significantly lower than that of the two literature methods, without adding additional network load. The network system is in a stable operation state, and users can quickly grasp their own required information, and the retrieval speed is also improved to a certain extent. It is proved that the proposed algorithm has high retrieval accuracy, can effectively reduce network load and achieve high-quality human-computer interactive information retrieval.

Over the last decade, architecture has witnessed a growing popularity for new computational tools such as parametric design environments (PDEs). Given their rapid evolution and development, expertise tends to become increasingly transient, and architects find themselves in a situation where they must constantly re-learn their tools. At the same time, access to information has become increasingly widespread. Self-learners can thus rely on information retrieval systems to address knowledge gaps. However, the inherent tool complexity has given rise to a new kind of knowledge. On the basis of the different types described by Anderson and Krathwohl, the authors have previously shown that conceptual knowledge is essential for teaching parametric design. In contrast, research on interactive information retrieval (IIR) has highlighted that procedural knowledge is preferred in create tasks like design. Consequently, it can be argued that in a self-learning situation, architects might not be adopting best practice in relation to knowledge retrieval, especially when considering the visual scripting nature of certain PDEs. The purpose of this paper is to observe cognitive patterns in knowledge search activities while designing in parametric environments and validate the integration of CLT and IIR for further research. We highlight the types of knowledge and sources architecture graduate students, novices in PDEs, search for during design over multiple sessions and why. The paper reports on three design tasks completed during a computational course that emphasized student's autonomy. A qualitative analysis of interviews reveals epistemic actions to fall prey to procedural information, which is in line with both IIR and CLT research. This research is part of a PhD project studying the impact of knowledge retrieval on architectural design when using PDEs. Eventually, it could raise awareness in education, research, and practice regarding information retrieval in architectural design.

This review examines a sample of interactive information retrieval (IR) systems within the framework of a design challenge set forth by John Bennett in 1971. Bennett directed his challenge to a group of information scientists who attended The User Interface for Interactive Search of Bibliographic Data Bases Workshop. During the workshop, participants exchanged their insights and experiences on various aspects of user interface requirements for interactive IR systems and discussed system design features that could result in the design of more effective user interfaces for information retrieval. The main goals of this review are to characterize interactive IR design trends over time, examine the extent to which IR systems have responded to Bennett's design challenge, and to suggest potential future research directions and challenges.

There is need for more foundational research in the development of interactive information retrieval systems. The results of a week long discussion by a group of multi­disciplinary researchers have reported here. A brief description of main activities and major recommendations of the workshop are reported here.

We report early results of our investigation of help-seeking behaviors during interactive information retrieval, with specific attention to one aspect of context, affective utterances made by searchers during the process of completing an assigned search task Searchers' utterances were coded as positive and negative assessments of the results of using automatic Help functionalities in two digital libraries. Although preliminary at this time, data presented in this paper indicate that affective utterances can be mapped to specific help-seeking events and therefore can be construed as important aspects of contextual feedback, worthy of further exploration.

PurposeThis study continues a long history of author co-citation analysis of the intellectual structure of information science into the time period of 2011–2020. It also examines changes in this structure from 2006–2010 through 2011–2015 to 2016–2020. Results will contribute to a better understanding of the information science research field.Design/methodology/approachThe well-established procedures and techniques for author co-citation analysis were followed. Full records of research articles in core information science journals published during 2011–2020 were retrieved and downloaded from the Web of Science database. About 150 most highly cited authors in each of the two five-year time periods were selected from this dataset to represent this field, and their co-citation counts were calculated. Each co-citation matrix was input into SPSS for factor analysis, and results were visualized in Pajek. Factors were interpreted as specialties and labeled upon an examination of articles written by authors who load primarily on each factor.FindingsThe two-camp structure of information science continued to be present clearly. Bibliometric indicators for research evaluation dominated the Knowledge Domain Analysis camp during both fivr-year time periods, whereas interactive information retrieval (IR) dominated the IR camp during 2011–2015 but shared dominance with information behavior during 2016–2020. Bridging between the two camps became increasingly weaker and was only provided by the scholarly communication specialty during 2016–2020. The IR systems specialty drifted further away from the IR camp. The information behavior specialty experienced a deep slump during 2011–2020 in its evolution process. Altmetrics grew to dominate the Webometrics specialty and brought it to a sharp increase during 2016–2020.Originality/valueAuthor co-citation analysis (ACA) is effective in revealing intellectual structures of research fields. Most related studies used term-based methods to identify individual research topics but did not examine the interrelationships between these topics or the overall structure of the field. The few studies that did discuss the overall structure paid little attention to the effect of changes to the source journals on the results. The present study does not have these problems and continues the long history of benchmark contributions to a better understanding of the information science field using ACA.

This workshop will provide a forum for researchers, practitioners and developers interested in user engagement and emotion in the context of human information interaction. Specifically, the workshop aims to address the following questions: “How do we ensure that the measurement of subjective information experience is robust and scalable?”, “How do we design interfaces for engaging and emotionally compelling experiences?”, and “How do we prevent disengagement?” The ability to answer these questions relies upon: a solid conceptual understanding of subjective experiences; robust, scalable approaches to measuring engagement; and the ability to utilize this knowledge in information systems and interface design. This three-part half-day workshop will include: talks by the organizers to ground the workshop’s themes; position paper presentations and design exemplars from attendees, and an interactive session focused on design scenarios and prototyping. The intersection of emotion and engagement with measurement and design in information interaction contexts is a timely issue for the iSchool community.

Cognitive work analysis (CWA) can play an important role in realizing convergence between research in human information interaction (HII) and information systems design. CWA has the potential to establish relations between various elements that have been fragmented in human information behavior research and in other HII areas. It can also connect theory with practice, various areas of research expertise, seemingly diverse areas of research, and various theoretical traditions and conceptual constructs. Moreover, CWA can help researchers decide about which variables to study. As an ecological approach, CWA can also be useful to the design of context-specific systems through its focus on environmental constraints.

It is an honour to present the program for the second ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2017), held in Oslo, Norway from March 7 to March 11, 2017. CHIIR offers the opportunity to present and discuss research on user-centered approachesto information retrieval, information access and information interaction, including studies of interactive systems, searcher behaviour, novel interaction paradigms, interface design, new evaluation methods, and a range of related areas. CHIIR is an interdisciplinary event in which researchers, students and practitioners working across several areas, including information retrieval, information science and human computer interaction, come together to think creatively about the challenges and opportunities afforded by digital information systems. Welcome to all the CHIIR-ists joining us this year! The CHIIR 2017 program consists of Full Papers (10 pages), Perspectives Papers (10 pages) and Short Papers (4 pages). We received a total of 112 submissions: 48 Full Papers, 9 Perspectives Papers and 55 Short Papers. Of these, we accepted 19 Full Papers (40%), 5 Perspectives Papers (56%) and 36 Short Papers (65%). We also accepted one Full Paper as a Short Paper. We were pleased to receive so many strong Perspectives Papers, which are meant to present novel ideas or insights, and we hope these will inspire some great discussions. Each Full and Perspectives paper is allocated a 30-minute presentation slot in the program. Short papers are presented as posters during a special evening session, beginning with a short boaster presentation. In addition to contributed papers, the CHIIR program features three keynote talks by prominent academic and industry researchers, representing the breadth of interests in the CHIIR community: Norbert Fuhr (University of Duisburg-Essen, Germany), Ann Blandford (University College London, UK) and Håkon Wium Lie (Opera Software, Norway). In addition to these speakers and the main conference program, CHIIR features a Doctoral Consortium, two Tutorials, and three Workshops. We would like to acknowledge the excellent work of the Organizing Committee, including the Doctoral Consortium Chair, Katriina Byström (Oslo and Akershus University College of Applied Sciences, Norway); the Workshops and Tutorials Chair, Preben Hansen (Stockholm University, Sweden), and the Proceedings Chair, Sampath Jayarathna (California State Polytechnic University Pomona, USA). The paper reviewing and selection process was enabled by an outstanding 12 member Senior Program Committee and a diverse and international general Program Committee consisting of 77 members. Our thanks and the credits for creating a high quality technical program go to them.

Under the Novel Intelligence from Massive Data program, Battelle is working in partnership with Stanford University's Knowledge Systems Laboratory and IBM's T.J. Watson. Research Center to develop a suite of technologies for knowledge discovery, knowledge extraction, knowledge representation, automated reasoning, and human information interaction. We envision an integrated analytic environment composed of a collection of analyst associates called “Knowledge Associates for Novel Intelligence (KANI).” One of Battelle's contributions to this environment is the design of an Information Interaction Associate, through which analysts will interact with other knowledge associates in KANI and actively construct and manipulate explicit models of the situations, events, actions, and scenarios that they analyze and hypothesize about during an analysis task. This paper reports on efforts to date towards the design of this component and efforts to develop and encode of a model of the intelligence analysis process.