Information Retrieval User Research Articles

Efektivitas Kegiatan Shelving terhadap Temu Kembali Informasi Pemustaka di Dinas Kearsipan dan Perpustakaan Provinsi Sumatera Barat

This research aims to eval_uate the effectiveness of shelving activities on user information retrieval_ at the Archives and Library Service of West Sumatra Province. Using descriptive methods, this research involved 99 respondents who were randomly selected using random sampling techniques. Data was collected through a questionnaire consisting of 32 statements. The research results show that the effectiveness of shelving has a positive and significant effect on user information retrieval_. The shelving variable obtained a percentage value of 71.78% (good category), while the information retrieval_ variable reached 76.18% (good category). The effectiveness of shelving has a significant effect on information retrieval_ by 52.5%. Although the overall assessment was positive, the research identified several areas requiring improvement, particularly in the aspects of accuracy of collection organization and shelving activities. Improvements in these aspects are expected to further increase user satisfaction and the effectiveness of information retrieval_ in the library.

Socio-cognitive Impact of Artifact Replacement

What happens when an artifact gets replaced by another artifact in a practice? In what respects, this artifact replacement impacts users, tasks and practice? This paper discusses socio-cognitive impact of artifact replacement in Indian native craft practice, Amritsar carpet-weaving which used a code-based design representation (talim) till few decades ago which it inherited from its historical cousin Kashmiri carpet-weaving. However, this DR got replaced with a graph-based DR called naksha around India's partition in 1947. The cognitive impact of this replaced artifact on users in information retrieval, team communication and coordination, and social impact in terms of design creativity of industry is reported. The paper emphasizes including historical analysis of artifact-evolution over time and their impact on user-interaction while analysing artifacts so that one may go beyond giving static snapshots of their current profiles and associations.

Personalized Music Recommendation Based on Interest and Emotion: A Comparison of Multiple Algorithms

Recommendation algorithms can greatly improve the efficiency of information retrieval for users. This article briefly introduced recommendation algorithms based on association rules and algorithms based on interest and emotion analysis. After crawling music and comment data from the NetEase Cloud platform, a simulation experiment was conducted. Firstly, the performance of the Back-Propagation Neural Network (BPNN) in the interest and emotion-based algorithm for recommending music was tested, and then the impact of the proportion of emotion weight between comments and music on the emotion analysis-based algorithm was tested. Finally, the three recommendation algorithms based on association rules, user ratings, and interest and emotion analysis were compared. The results showed that when the BPNN used the dominant interest and emotion and secondary interest and emotion as judgment criteria, the accuracy of interest and emotion recognition for music and comments was higher. When the proportion of interest and emotion weight between comments and music was 6:4, the interest and emotion analysis-based recommendation algorithm had the highest accuracy. The interest and emotion-based recommendation algorithm had higher recommendation accuracy than the association rule-based and user rating-based algorithms, and could provide users with more personalized and emotional music recommendations.

Reflection on future directions: a systematic review of reported limitations and solutions in interactive information retrieval user studies

PurposeThe purpose of this paper is to understand how users behave and evaluate how systems with users are essential for interactive information retrieval (IIR) research. User study methodology serves as a primary approach to answering IIR research questions. In addition to designing user study procedures, understanding the limitations of varying study designs and discussing solutions to the limitations is also critical for improving the methods and advancing the knowledge in IIR.Design/methodology/approachGiven this unresolved gap, we apply the faceted framework developed by Liu and Shah (2019) in systematically reviewing 131 IIR user studies recently published (2016–2021) on multiple IR and information science venues.FindingsOur study achieve three goals: (1) extracting and synthesizing the reported limitations on multiple aspects of user study (e.g. recruitment, tasks, study procedures, system interfaces, data analysis methods) under associated facets; (2) summarizing the reported solutions to the limitations; (3) clarifying the connections between types of limitations and types of solutions.Practical implicationsThe bibliography of user studies can be used by students and junior researchers who are new to user-centered IR studies as references for study design. Our results can facilitate the reflection and improvement on IR research methodology and serve as a checklist for evaluating customized IIR user studies in varying problem spaces.Originality/valueTo our knowledge, this work is the first study that systematically reviews the study limitations and solutions reported by IIR researchers in articles and empirically examines their connections to different study components.

Peranan Pustakawan Dalam Sistem Temu Balik Informasi di Perpustakaan Sekolah SMA N 1 Bukit Sundi

The main problem in this thesis is the role of the librarian in improving the information retrieval system in the school library of SMA N 1 Bukit Sundi. This study aims to identify and explain the role of librarians in information retrieval systems, and what obstacles are faced by librarians and users in information retrieval systems.The research method used in this research is the method qualitative research using descriptive type. Collection technique The data used are observation, interviews, and documentation. Technique The data analysis used is data reduction, data presentation, data withdrawal conclusion and verification. Guarantee the validity of the data in this study using triangulation of techniques, sources and time. The results of the study concluded that the librarian plays an important role in the information retrieval system. The role of the librarian in the information retrieval system is generally in the processing section such as cataloging, classifying library materials, and determining subject headings to facilitate data entry and information retrieval in the retrieval system. In addition, in terms of processing library materials, book inventory activities, labeling, barcode attachment, and book bag attachment are also carried out. In the service section, the librarian's role is more about returning and borrowing library materials,provide guidance to users regarding procedures for information retrieval, use of libraries, use of independent services and librarians also serve users if someone comes directly to ask the librarian about the information needed quickly and accurately. Librarians also act as educators (educators) as educational librarians, providing education such as mini-meetings once a year to provide education to users on how to use catalogs, managers, administrators, and also supervisors in information retrieval systems.Keywords: Librarian, Retrieval System

Research on Information Retrieval Effectiveness of University Scientific Researchers Based on Mental Model

The information retrieval behavior of scientific researchers is a behavior that is affected by multiple factors such as cognition, emotion, task, and user type and has its unique cognitive characteristics. In the context of scientific research, this paper conducts research on the information retrieval behavior of scientific researchers and analyzes the three levels of user mental model “user cognition, user behavior, and user emotion.” According to the mental model construction process, define the user segmentation of basic tasks, formulate recruitment plan, set interview scope, analyze data, construct mental model, product adjustment and gap analysis, export structure seven steps, construct the mental model of scientific research workers’ information retrieval, carry out research on the information retrieval efficiency of scientific researchers, describe the user portrait based on the mental model, and put forward strategies to improve the efficiency of user information retrieval.

An intelligent personalized web user information retrieval using partial least squares and artificial neural networks

An intelligent personalized web user information retrieval using partial least squares and artificial neural networks

Information retrieval interfaces in virtual reality-A scoping review focused on current generation technology.

The Information Retrieval user experience has remained largely unchanged since its inception for computers and mobile devices alike. However, recent developments in Virtual Reality hardware (pioneered by Oculus Rift in 2013) could introduce a new environment for Information Retrieval. This paper reports the results of a Scoping Literature Review (PRISMA-ScR) by rigorously examining the entire body of relevant literature with reproducible methods. The following research questions are answered: "What prototypes and concepts of Virtual Reality Information Retrieval systems with current generation hardware exist?", "How are user interaction and especially user input realised in these systems?", "What Retrieval features are used in these systems?", "How are search results displayed in these systems?" and "Can these VR IR systems compare to traditional (non-VR) IR systems?". After querying Google Scholar, Scopus and Web of Science, 1042 documents were reviewed in depth. Key features and attributes of the systems are summarised and discussed. Sketches of the user interfaces are included as well. The 30 documents that were relevant to the research questions include 16 distinct systems or theories. They discuss and utilise several user input technologies, ranging from controllers, voice input or hand tracking. Although conventional retrieval features are less common, systems enable retrieval of literature, 3D objects, images, books and texts and arrange them in a virtual space (e.g. as grids, arcs or maps). Finally, many of these systems were compared to conventional counterparts through user evaluation (n = 10). Most found user task times to be shorter or equal (n = 5, n = 3). In the seven papers that measured user performance (rate of correct solutions), three reported better performance (one equal). Notably, users always were more satisfied with the Virtual Reality systems compared to conventional ones. Possible limitations of these evaluations are demographic selection and the quality of baseline systems (control).

AQtpUIR: Adaptive query term proximity based user information retrieval

Information-seeking process primarily relies on the relevance manifestation and usually based on term statistics. Document-term statistics are dominant, e.g. term-frequency (TF), inverse document frequency (IDF), document length (DL), etc. Query Term Proximity (QTP) is mostly under-explored for the relevance estimation in the information retrieval. In this paper, we systematically review the lineage of the notion of QTP and proposed a novel framework for relevance estimation. The proposed framework is referred as Adaptive QTP based User Information Retrieval (AQtpUIR), is intended to promote the relevant documents. Here, the relevance estimation is a weighted combination of statistics. The notions ‘term-term query proximity’ is a simple aggregation of contextual aspects of user search in relevance estimates and query formation. Intuitively, QTP is derived via pre-processing, inherent to indexing and text-processing, and utilized to promote the extracted documents among all retrieved documents. Thus also balance the exploitation-exploration tradeoff. The adaption of QTP balance the traditional retrieval tradeoff, e.g. relevance, novelty, result diversity (Coverage and Topicality), and highlight various inherent challenges and issue of the proposed work.

Rancang Bangun Sistem Informasi Situs Bersejarah Berbasis Web

Historic sites are a form of heritage and cultural heritage of ancestors that have value for the life of the nation today and in the future. Magelang City is one city that has many historic sites that have not been optimally managed. The k-medoid algorithm is a method used in creating groups based on objects as representatives (medoid) which function as cluster centers for each cluster. In this research, web-based historic site information system design in Magelang City is carried out. Through the information system that has been built to provide a friendly user information retrieval that has many advantages such as searching, grouping and information data accessed by visitors.

Probability model of sensitive similarity measures in information retrieval

In today’s Internet age, a lot of data is stored and used, which is very important. In people’s daily life, if these data are sorted, information retrieval technology will be used, and in information retrieval, some information retrieval inaccuracies often appear. Information retrieval model is an important framework and method for fast, complete, and accurate user information retrieval. With the rapid development of information technology, great changes have taken place in people’s production and life. Various information network technologies are widely used in people’s lives. The resulting flow of information shows explosive growth, information retrieval. User requirements are getting higher and higher. How to complete personalized information retrieval in a large amount of mixed information, so that retrieval technology can help us obtain effective retrieval results, has become a realistic problem worth exploring. In this article, the application of probability model based on sensitive similarity measure in information retrieval model is analyzed, and a similarity measure algorithm based on spectral clustering is proposed. By improving the similarity measure, the sensitivity problem of scale parameters is overcome and the retrieval precision is improved. In order to better reflect the superiority of the proposed algorithm, this article compares with ng-jordan-weiss (NJW) and deep sparse subspace clustering (DSSC) algorithms. The experimental results show that the proposed algorithm is superior to NJW and DSSC algorithms for different data sets in different evaluation indicators (Rand and F-measure).

Semantic PDF Segmentation for Legacy Documents in Technical Documentation

The most common format to store and provide technical documentation is PDF. However, due to the unstructured nature of the format these documents are often excluded from a granular semantic access. While more and more companies are implementing XML-based component content management systems which can deliver annotated structured content, older legacy documents remain in their monolithic form.We developed a new approach which segments PDF documents into semantically related sections via classification knowledge gained from structured training content. This approach based on machine learning is independent from any formatting information or visual clues.In this paper, we take the results from multiple previous works and combine them into a holistic procedure model. We introduce a parameterizable range finding algorithm to refine segment detection and provide a RDF-based format to exchange the generated metadata which can then be used to improve information retrieval for users.

Context-aware query expansion method using Language Models and Latent Semantic Analyses

One of the key difficulties for users in information retrieval is to formulate appropriate queries to submit to the search engine. In this paper, we propose an approach to enrich the user's queries by additional context. We used the Language Model to build the query context, which is composed of the most similar queries to the query to expand and their top-ranked documents. Then, we applied a query expansion approach based on the query context and the Latent Semantic Analyses method. Using a web test collection, we tested our approach on short and long queries. We varied the number of recommended queries and the number of expansion terms to specify the appropriate parameters for the proposed approach. Experimental results show that the proposed approach improves the effectiveness of the information retrieval system by 19.23 % for short queries and 52.94 % for long queries according to the retrieval results using the original users' queries.

Automated Computational Cognitive-Modeling

The information architecture of websites is the most important remaining source of usability problems. Therefore, this research explores automated cognitive computational analysis of the information architecture of large websites as a basis for improvement. To support goal-specific analysis, an enhanced model of web navigation was implemented with a novel database-oriented approach. Web navigation was simulated on the information architecture of two large sites. With the improved labeling system of the information architecture, simulation results showed a significant reduction in navigation problems. The results of two experiments demonstrate that sites with improved information architecture result in better outcomes of user information retrieval. Our database-oriented approach is extensible, allowing non-goal-specific analysis, modeling of nontext media content, and analysis of the organization- and navigation systems of information architectures.

Introduction to the special issue on search intents and diversification

This special issue of the Information Retrieval journal is focused on the topic of query intents and diversification within search engines. Indeed, information retrieval users have diverse search needs, and the level of detail given in the user’s search query can differ widely depending on how clear the underlying information need itself is, the user’s search environment (e.g. input device), and how difficult it is for the user to express the need in the form of a query. For these reasons, many queries are ambiguous and/or underspecified. In light of this, research in accommodating different search intents has received a lot of attention lately. For example, major conferences like SIGIR, WWW and WSDM have begun to see papers on search result diversification, which aims to capture different user needs within one entry-point search result page. This problem was discussed intensively at the ECIR 2011 and WSDM 2012 Diversity in Document Retrieval Workshops. Also, in recent years, the TREC Web (2009–2012) and TREC Blog (2010) tracks have measured the diversity of participating systems in retrieving web pages and blog posts, respectively. Moreover, the recent INTENT tasks at NTCIR-9 and NTCIR-10 tackled not only search result diversification but also the task of mining intents given a query. The aim of this special issue is to highlight the advances and clarify the future goals in the ares of search intents and diversification. In particular, the articles included in this special issue address two areas within this vision, namely the identification of query

Understanding searchers' perception of task difficulty: Relationships with task type

We report findings that help us better understand the difficulty of tasks which involve information seeking, retrieving, gathering, and use. We examined the data gathered from two interactive information retrieval user studies on how users' perception of task difficulty changes before and after searching for information to solve tasks, and how the difficulty of tasks relates with users' background, previous experience with the tasks, and knowledge of the task topics, etc. The two studies employed carefully designed tasks with different types along several dimensions: task structure (subtasks being dependent upon or parallel with each other), task goal in quality (being specific or amorphous), and naming (being named or unnamed). It was found that while in some types of tasks, users' perceptions of task difficulty did not change before and after working on the tasks, in others, this did, either increasing or decreasing. Specifically, in the dependent-structured task, this did not change. In the parallel-structured or specific/named task, it decreased. In the amorphous/unnamed task, it increased. We also found that users' background factors do not normally correlate with their perceived task difficulty, or perceived difficulty change. In addition to helping understand the dynamic and complex nature of task difficulty, our findings have implications for system design that can provide assistance to users with their search and task solving strategies.

Drug information portal in Europe: information retrieval with multiple health terminologies.

The objective of this work is the creation of a bilingual (French/English) drug information portal (DIP), in a multi-terminological context. The development of the DIP was based on the CISMeF portal, which catalogues and indexes the most important and quality-controlled sources of institutional health information in French. DIP has created specific functionalities related to drug and used specific drugs terminologies and classifications: the ATC classification, the CAS numbers, the French codes CIS, and CIP, as well as trade names and the International Nonproprietary Names of the drugs. DIP is the result of collaboration between the CISMeF team and the VIDAL private Company, specialized in drug information. DIP is conceived to facilitate the user information retrieval using several health terminologies. In the framework of the drug field, using multi-terminological context, indexing drugs with the appropriate codes or/and terms revealed to be very important to have the appropriate information storage and retrieval.

An Investigation of User Behaviour Consistency for Context-Aware Information Retrieval Systems

Users interact with the Internet in dynamic environments that require the IR system to be context aware. Modern IR systems take advantage of user location, browsing history or previous interaction patterns, but a significant number of contextual factors that impact the user information retrieval process are not yet available. Parameters like the emotional state of the user and user domain expertise affect the user experience significantly but are not understood by IR systems. This article presents results of a user study that simplifies the way context in IR and its role in the systems’ efficiency is perceived. The study supports the hypothesis that the number of user interaction contexts and the problems that a particular user is trying to solve is related to lifestyle. Therefore, the IR system’s perception of the interaction context can be reduced to a finite set of frequent user interactions.

Web‐application composition through direct editing of Web documents and multiplexing of information access scenarios

AbstractIn order to support user information retrieval on the Web, a framework is needed in which a user can define various types of data links as necessary by extracting only the necessary components from a Web application and then create a new compound document. This compound document refers to a document that includes services and tools embedded in it. In this research, the authors propose a framework which allows for clipping the structural elements of a Web application and directly manipulating the data linkages using formulas. As a result, the user can clip these components into cells from different Web applications, and then by linking them, create a unique compound document. Moreover, the authors provide a framework for cloning the clipped cells in order to compare the results of various different searches. Furthermore, in this paper the authors describe a method to use a word processing document or spreadsheet as a destination for embedding the clipped components, and function linking for these documents and the clipped cells. As a result, the created custom complex document can be reused and shared more easily. © 2007 Wiley Periodicals, Inc. Syst Comp Jpn, 38(12): 1–13, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.20861

Grainger Engineering Library: An Object-Enhanced User Interface for Information Retrieval

Summary Telnet and HTML-based information retrieval user interfaces provide searchers with neither the power nor the flexibility required for effectively searching multiple databases. Nor do they exploit the existing power of PCs or make good use of client-server technology as a whole. lODyne is an example of an information retrieval client that views databases and queries as objects which you can combine arbitrarily. It has a commandless, hypertextual user interface incorporating modelessness, direct manipulation, feedback, and object persistence. It uses multiple windows to show multiple views of databases simultaneously, and allows you to arbitrarily juxtapose these views. Besides bibliographic retrieval, lODyne provides navigational tools for subject thesauri, classification systems, keyword-in-context (KWIC) databases, and other term suggestion services, represented as distributed objects which are all integrated into a seamless drag-and-drop environment. Persistent representations of sets of queries and repositories can be saved and shared among lODyne users. 10-Dyne demonstrates that, with recent advances in computer and network hardware, as well as object-oriented development environments, entire information systems can be designed around the needs of users rather than the limitations of technology.