Collaborative Information Retrieval Research Articles

Model of collaborative information retrieval behavior using information systems among academic researchers of medical sciences

Aim The purpose of this study was to analyze the collaborative information retrieval (CIR) behavior among faculty members of research centers based in the University of Medical Sciences to present a structural model. Methodology The type of this experimental study was based on a pretest-posttest with the control group. Data were collected using a questionnaire, and the participants were selected by stratified random sampling. Out of a total of 73 participants, there were 42 people in the intervention group and 31 participants in the control group. Findings The variables of awareness, information sharing, division of labor, and team communication had a significant positive relationship with the team collaboration (p < 0.05), collaboration had effect on the evaluation of retrieved information with a significant positive relationship (p < 0.05). Conclusion Based on the findings, CIR is the set of activities that can include factors such as the ability to share the obtained knowledge, analyze the retrieved information, communicate, and collaborative awareness. The structural model confirmed our findings that developing the interactive and synergies capabilities of research team members to increase collaboration through a network-based structure reduces the loss of stored collective knowledge and also accelerates the process of access to information resources, and required content. Originality This research has carried on as the one of the first studies on collaborative information retrieval behavior with an experimental method in Iran and many others countries. A considerable point in the present study was assessing the nature of CIR behavior from the perspective of human behaviors, which was mentioned as a very important approach in information science. Accordingly, a human behavioral approach to information retrieval was considered and strengthened, regardless of technical aspects. Another strength of this study was the model extracted from our findings which have emphasized specifically CIR as specific and dynamic activities.

A Scoping Review of Collaborative Information Behavior

Many researchers have mischaracterized collaborative information behavior (CIB) with its sub-processes, including collaborative information seeking (CIS) and collaborative information retrieval (CIR). To learn about the most prominent CIB definitions, the phases involved in the CIB process, and the various collaboration tools that facilitate CIB, we sifted through a wide range of LIS research papers. Using a scoping review to correspond with the research questions, we conducted several iterations to exclude irrelevant studies while concurrently including pertinent ones. The “C5 model of collaboration” developed by Shah provides a framework for coding our data during content analysis and concept mapping. Our findings indicate that CIB has no generally adopted definition. Additionally, traditional workplace tools and technologies are the collaborative tools utilized for various collaborative activities. More CIB research is needed in the information science field to stay ahead of the rapid growth of collaborative AI technologies, particularly those that foster human-AI collaborations.

Report on the Second International Workshop on the Evaluation on Collaborative Information Seeking and Retrieval (ECol?2017 @ CHIIR)

The 2nd workshop on the evaluation of collaborative information retrieval and seeking (ECol) was held in conjunction with the ACM SIGIR Conference on Human Information Interaction & Retrieval (CHIIR) in Oslo, Norway. The workshop focused on discussing the challenges and difficulties of researching and studying collaborative information retrieval and seeking (CIS/CIR). After an introductory and scene setting overview of developments in CIR/CIS, participants were challenged with devising a range of possible CIR/CIS tasks that could be used for evaluation purposes. Through the brainstorming and discussions, valuable insights regarding the evaluation of CIR/CIS tasks become apparent ? for particular tasks efficiency and/or effectiveness is most important, however for the majority of tasks the success and quality of outcomes along with knowledge sharing and sense-making were most important ? of which these latter attributes are much more difficult to measure and evaluate. Thus the major challenge for CIR/CIS research is to develop methods, measures and methodologies to evaluate these high order attributes.

Non-Uniform Information Access in Collaborative Information Retrieval

Although there has been a great deal of research into Collaborative Information Retrieval/Seeking (CIR/S), the majority has assumed that team members in a collaborative search team always have the same level of unrestricted access to information. However, observations from different domains such as healthcare, business, government, etc. have suggested that collaboration sometimes involves people with differing levels of access to information. This type of scenario has been referred to as Multi-Level Collaborative Information Retrieval (MLCIR). As well as a support for collaboration, MLCIR must consider information flow, security and shareability between collaborators. Therefore, existing CIR/S interface components and concepts (e.g. awareness, division of labour, persistence, etc.) may not be directly applicable to MLCIR. To the best of our knowledge, there has not been any systematic evaluations to investigate the impact of MLCIR on search outcomes and to provide user-centred design recommendations for MLCIR interfaces. To address this gap, a number of studies were conducted using real-world MLCIR examples as scenarios. This thesis highlights four research objectives; these are: 1) to investigate the impact of different collaborative search strategies and MLCIR scenarios on search outcomes using a user simulation approach, 2) to develop a preliminary MLCIR interface and investigate the impact of MLCIR scenarios on search outcomes using a user study, 3) to investigate the impact of existing CIR concepts on MLCIR search outcomes using a user study, and 4) to develop and evaluate a working prototype of an MLCIR interface that supports users for asynchronous collaboration. These investigations followed an iterative approach until a final MLCIR interface could be produced. The first study was a user simulated study which allowed us to test a large number of variables and to pick prominent ones for further user studies. It was found that when relevance feedback search strategies were used, search performance of non-full access (where team members had 90% access to collection) outperformed full access (where team members had 100% access to collection). This simulated study also fulfilled the first research objective. Next, a preliminary user study was conducted using variables selected based on the findings of the simulated study. This study uncovered a number of interface components, and awareness concepts such as query awareness, result awareness and team awareness that could be used to support users in MLCIR scenarios. This user study addressed the second research objective. Based on findings from this user study, two further user studies were conducted where we evaluated a number of interface components implemented to support query awareness, result awareness and team awareness. Results suggested that having access to query properties and result properties in MLCIR scenarios can leverage team members? search performance. These two user studies addressed the third research objective. Finally, a working MLCIR interface was built based on the findings elicited from our previous user studies. The interface was then evaluated using the web and non-uniform information access scenarios. The results showed that blacklisting search terms had a significant negative impact on search outcome than blacklisting documents (f-measure: 0.04 vs 0.197). This study fulfilled the final research objective. All five studies presented in this thesis provided us with an increasing understanding of how to develop an MLCIR interface that is usable and helpful for users. As a final product, a working MLCIR interface was produced which could provide collaborating users with useful awareness information without disclosing any sensitive data. Overall, this thesis provided important new design suggestions and showed reusability of CIR components for MLCIR interfaces, something that has never been demonstrated before. The interfaces, experimental designs and findings including design suggestions that are presented in this thesis serve as novel guidelines for further investigations into MLCIR.

Beyond traditional collaborative search: Understanding the effect of awareness on multi-level collaborative information retrieval

Although there has been a great deal of research into Collaborative Information Retrieval (CIR) and Collaborative Information Seeking (CIS), the majority has assumed that team members have the same level of unrestricted access to underlying information. However, observations from different domains (e.g. healthcare, business, etc.) have suggested that collaboration sometimes involves people with differing levels of access to underlying information. This type of scenario has been referred to as Multi-Level Collaborative Information Retrieval (MLCIR). To the best of our knowledge, no studies have been conducted to investigate the effect of awareness, an existing CIR/CIS concept, on MLCIR. To address this gap in current knowledge, we conducted two separate user studies using a total of 5 different collaborative search interfaces and 3 information access scenarios. A number of Information Retrieval (IR), CIS and CIR evaluation metrics, as well as questionnaires were used to compare the interfaces. Design interviews were also conducted after evaluations to obtain qualitative feedback from participants. Results suggested that query properties such as time spent on query, query popularity and query effectiveness could allow users to obtain information about team's search performance and implicitly suggest better queries without disclosing sensitive data. Besides, having access to a history of intersecting viewed, relevant and bookmarked documents could provide similar positive effect as query properties. Also, it was found that being able to easily identify different team members and their actions is important for users in MLCIR. Based on our findings, we provide important design recommendations to help develop new CIR and MLCIR interfaces.

On the Collaboration Support in Information Retrieval

Collaborative Information Retrieval (CIR) is a well-known setting in which explicit collaboration occurs among a group of users working together to solve a shared information need. This type of collaboration has been deemed as beneficial for complex or exploratory search tasks. With the multiplicity of factors impacting on the search effectiveness (e.g., collaborators’ interactions or the individual perception of the shared information need), CIR gives rise to several challenges in terms of collaboration support through algorithmic approaches. More particularly, CIR should allow us to satisfy the shared information need by optimizing the collaboration within the search session over all collaborators, while ensuring that both mutually beneficial goals are reached and that the cognitive cost of the collaboration does not impact the search effectiveness. In this survey, we propose an overview of CIR with a particular focus on the collaboration support through algorithmic approaches. The objective of this article is (a) to organize previous empirical studies analyzing collaborative search with the goal to provide useful design implications for CIR models, (b) to give a picture of the CIR area by distinguishing two main categories of models using the collaboration mediation axis, and (c) to point out potential perspectives in the domain.

Information Retrieval Model using Uncertain Confidence's Network

This paper proposes a new relevance feedback approach to collaborative information retrieval based on a confidence's network, which performs propagation relevance between annotations terms. The main contribution of our approach is to extract relevant terms to reformulate the initial user query considering the annotations as an information source. The proposed model introduces the concept of necessity that allows determining the terms that have strong association relationships. The authors estimated the association relationship to a measure of a confidence. Another contribution consists on determining the relevant annotations for a given evidence source. Since the user is over whelmed by a variety of contradictory annotations on even one which are far from the original subject, the authors' model proceed filtering these annotations to determine the relevant one and then it classify them by grouping those related semantically. The experimental study conducted on different queries gives promoters results. They show very encouraging results that could reach an improvement rate.

Report on the First International Workshop on the Evaluation on Collaborative Information Seeking and Retrieval (ECol'2015)

The workshop on the evaluation of collaborative information retrieval and seeking (ECol) was held in conjunction with the 24th Conference on Information and Knowledge Management (CIKM) in Melbourne, Australia. The workshop featured three main elements. First, a keynote on the main dimensions, challenges, and opportunities in collaborative information retrieval and seeking by Chirag Shah. Second, an oral presentation session in which four papers were presented. Third, a discussion based on three seed research questions: (1) In what ways is collaborative search evaluation more challenging than individual interactive information retrieval (IIIR) evaluation? (2) Would it be possible and/or useful to standardise experimental designs and data for collaborative search evaluation? and (3) For evaluating collaborative search, can we leverage ideas from other tasks such as diversified search, subtopic mining and/or e-discovery? The discussion was intense and raised many points and issues, leading to the proposition that a new evaluation track focused on collaborative information retrieval/seeking tasks, would be worthwhile.

MineRank: Leveraging users’ latent roles for unsupervised collaborative information retrieval

Research on collaborative information retrieval (CIR) has shown positive impacts of collaboration on retrieval effectiveness in the case of complex and/or exploratory tasks. The synergic effect of accomplishing something greater than the sum of its individual components is reached through the gathering of collaborators’ complementary skills. However, these approaches often lack the consideration that collaborators might refine their skills and actions throughout the search session, and that a flexible system mediation guided by collaborators’ behaviors should dynamically adapt to this situation in order to optimize search effectiveness. In this article, we propose a new unsupervised collaborative ranking algorithm which leverages collaborators’ actions for (1) mining their latent roles in order to extract their complementary search behaviors; and (2) ranking documents with respect to the latent role of collaborators. Experiments using two user studies with respectively 25 and 10 pairs of collaborators demonstrate the benefit of such an unsupervised method driven by collaborators’ behaviors throughout the search session. Also, a qualitative analysis of the identified latent role is proposed to explain an over-learning noticed in one of the datasets.

Collaborative information retrieval model based on fuzzy confidence network

The Web information is too heterogeneous that users have difficulties to retrieve their needed information: text, image or video. Indeed, the collaborative work presents one solution proposed to solve this problem. Collaborative retrieval enables the retrieval histories’ sharing between users havin g the same profile across multiple tools such as annotations. However the user has always problems in choosing the terms to form his query. This paper has proposed collaborative Information Retrieval Model based on Fuzzy Confidence Network. Our approach allows the detection of relevant annotations to a given evidence source. These annotations are next filtered to determine which are relevant to consider them as a new source of information that describes the document used to improve collaborative retrieval performance. We then measure the semantic relationships between terms which will be translated by the propagation of confidence. Experiments were conducted on different queries, showing very encouraging results that could reach an improvement rate.

Understanding tourists' collaborative information retrieval behavior to inform design

With the rapid development of information and communication technologies, people are increasingly referring to web information to assist in their travel planning and decision making. Research shows...

Understanding tourists' collaborative information retrieval behavior to inform design

With the rapid development of information and communication technologies, people are increasingly referring to web information to assist in their travel planning and decision making. Research shows that people conduct collaborative information searches while planning their travel activities online. However, little is known in depth about tourists' online collaborative search. This study examines tourists' collaborative information search behavior in detail, including their search stages, online search strategies, and information flow breakdowns. The data for analysis included pre‐ and postsearch questionnaires, web search and chat logs, and postsearch interviews. A model of tourist collaborative information retrieval was developed. The model identified collaborative planning, collaborative information searching, sharing of information, and collaborative decision making as four stages of tourists' collaborative search. The results show that tourists collaborated by planning their search strategies, dividing search tasks into subtasks and allocating workload, using search queries and URL links recommended by teammates, and discussing search results together. Related personal knowledge and experiences appeared important in trip planning and collaborative information search. During the collaborative search, tourists also encountered various information flow breakdowns in different search stages. These were classified and their effects on collaborative information search were reported. Implications for system design in support of collaborative information retrieval in travel contexts are also discussed.

Qualitative analysis of user experience in a 3D virtual environment

ABSTRACTThis paper describes elements of user experience of a collaborative 3D immersive virtual information management environment. We detail those elements that are seen to both improve and deteriorate user experience, and provide design guidance for researchers and designers. We designed the 3D virtual environment in the Virtual Collaboration Arena (VirCA) collaborative space specifically to study the collaborative information retrieval and management behaviors of users. We conducted 117 interviews and then analyzed the data using a qualitative content analysis to identify the main elements of user experience. While participants generally reacted positively to the environment, they also mentioned a few distracting usability problems. Applying the results in the further development of VirCA can create a higher level of user experience and more effective collaboration.

On domain expertise-based roles in collaborative information retrieval

Collaborative information retrieval involves retrieval settings in which a group of users collaborates to satisfy the same underlying need. One core issue of collaborative IR models involves either supporting collaboration with adapted tools or developing IR models for a multiple-user context and providing a ranked list of documents adapted for each collaborator. In this paper, we introduce the first document-ranking model supporting collaboration between two users characterized by roles relying on different domain expertise levels. Specifically, we propose a two-step ranking model: we first compute a document-relevance score, taking into consideration domain expertise-based roles. We introduce specificity and novelty factors into language-model smoothing, and then we assign, via an Expectation–Maximization algorithm, documents to the best-suited collaborator. Our experiments employ a simulation-based framework of collaborative information retrieval and show the significant effectiveness of our model at different search levels.

EzDL: Collaborative Information Seeking and Retrieval in a Heterogeneous Environment

Most information seeking and retrieval systems are designed for individual use, and prototype collaborative systems are too limited to support use in heterogeneous environments. Easy Access to Digital Libraries (ezDL) attempts to bridge this gap by integrating familiar information sharing and management functions with communication tools into a flexible, scalable network in which individuals and groups function as nodes.

Collaborative information seeking

The notions that information seeking is not always a solitary activity and that people working in collaboration for information intensive tasks should be studied and supported have become more prevalent in recent years. Several new research questions, methodologies, and systems have emerged around these notions that may prove to be useful beyond the field of collaborative information seeking (CIS), with relevance to the broader area of information seeking and behavior. This article provides an overview of such key research work from a variety of domains, including library and information science, computer‐supported cooperative work, human‐computer interaction, and information retrieval. It starts with explanations of collaboration and how CIS fits in different contexts, emphasizing the interactive, intentional, and mutually beneficial nature of CIS activities. Relations to similar and related fields such as collaborative information retrieval, collaborative information behavior, and collaborative filtering are also clarified. Next, the article presents a synthesis of various frameworks and models that exist in the field today, along with a new synthesis of 12 different dimensions of group activities. A discussion on issues and approaches relating to evaluating various parameters in CIS follows. Finally, a list of known issues and challenges is presented to provide an overview of research opportunities in this field.

Toward a model of collaborative information behavior in organizations

There is increasing interest in topics at the nexus of collaboration and information behavior. A variety of studies conducted in organizational settings have provided us with key insights about the collaborative aspects of seeking, retrieving, and using information. Researchers have used a range of terms, including collaborative information seeking (CIS), collaborative information retrieval (CIR), collaborative search, collaborative sensemaking, and others to describe various pertinent activities. Consequently, we lack conceptual clarity concerning these activities, leading to a tendency to use terms interchangeably when in fact they may be referring to different issues. Here, we offer collaborative information behavior (CIB) as an umbrella term to connote the collaborative aspects of information seeking, retrieval, and use. We provide the contours of a model of CIB synthesized from findings of past studies conducted by our research team as well as other researchers. By reanalyzing and synthesizing the data from those studies, we conceptualize CIB as comprised of a set of constitutive activities, organized into three broad phases—problem formulation, collaborative information seeking, and information use. Some of the activities are specific to a particular phase, whereas others are common to all phases. We explain how those constitutive activities are related to one another. Finally, we discuss the limitations of our model as well as its potential usefulness in advancing CIB research.

Iterative design of a collaborative 3D virtual information management environment

AbstractThe goal of this paper is to describe the design of a collaborative 3D immersive virtual information management environment. This environment was developed in order to study collaborative information retrieval behavior by users. In the first phase of research we designed and developed this environment in the Virtual Collaboration Arena (VirCA) collaborative space.

Collaborative Information Retrieval Framework Based on FCA

Abstract In Collaborative Information Retrieval, for multiple sub-text databases, sub-lattices are constructed with the incremental update algorithms. Then, similarity measuring is used to match the formal concepts, use merging to obtain new concepts after finding provisional concept sets. Similarity matching is used to the new concepts to get the final result set. The framework can work under a distributed environment and an an imprecise way is used when matching the query words, which considered the convenience of users.

The impact of friendship on synchronous collaborative retrieval tasks in the primary school

Two experiments aim at describing the impact of friendship during a synchronous collaborative information retrieval (SCIR) with young pupils (recruited in Grade 3). In the first study, 68 pupils were asked to look for 13 answers in one of the three following conditions: on an individual basis (condition 'Single'), as part of a designed duo with social friendship (condition 'Affinity +'), or as part of a designed duo without social friendship (condition 'Affinity −'). In the second experiment, we investigated more precisely the impact of friendship on verbal interactions between partners. Main results obtained in these two experiments are the following: (1) pairs retrieved effectively more answers, more correct answers and were more efficient than singles; (2) pairs composed of pupils without social friendship retrieved more answers, more correct answers and were more efficient than pairs composed by friends; (3) pairs composed of friends produced significantly more irrelevant queries; and (4) pairs composed of friends produced more verbalisations related to conflicts, while pairs composed of pupils without social friendship are engaged in a great deal of consensus seeking. Finally, educational implications are discussed. [ABSTRACT FROM AUTHOR]