Misuse detection for information retrieval systems

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

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.

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.

Most books on information-seeking neglect the human side to focus solely on the technical aspects of retrieval systems. This book is the first to provide an information science perspective on information retrieval, with a focus on user behavior and needs. Beginning with the history of information retrieval, coverage goes on to consider behavioral models and interactive techniques as well as the design, implementation and evaluation of information retrieval interfaces. This comprehensive book will be the go-to for LIS students and professionals hoping to better appreciate and utilize information retrieval systems, theories, and practices. Contents Interactive information retrieval : history and background / Colleen Cool and Nicholas J. Belkin Information behavior and seeking / Peiling Wang Task-based information searching and retrieval / Elaine G. Toms Approaches to investigating information interaction and behaviour / Raya Fidel Information representation / Mark D. Smucker Access models / Edie Rasmussen Evaluation / Kalervo Jarvelin Interfaces for information retrieval / Max Wilson Interactive techniques / Ryen W. White Web retrieval, ranking and personalization / Jaime Teevan and Susan Dumais Recommendation, collaboration and social search / David M. Nichols and Michael B. Twidale Multimedia : behaviour, interfaces and interaction / Haiming Liu, Suzanne Little and Stefan Ruger Multimedia : information representation and access / Suzanne Little, Evan Brown and Stefan Ruger

This chapter aims to master web mining and Information Retrieval (IR) in the digital age, thus describing the overviews of web mining and web usage mining; the significance of web mining in the digital age; the overview of IR; the concept of Collaborative Information Retrieval (CIR); the evaluation of IR systems; and the significance of IR in the digital age. Web mining can contribute to the increase in profits by selling more products and by minimizing costs. Web mining is the application of data mining techniques to discover the interesting patterns from web data in order to better serve the needs of web-based multifaceted applications. Mining web data can improve the personalization, create the selling opportunities, and lead to more profitable relationships with customers in global business. Web mining techniques can be applied with the effective analysis of the clearly understood business needs and requirements. Web mining builds the detailed customer profiles based on the transactional data. Web mining is used to create the personalized search engines which can recognize the individuals' search queries by analyzing and profiling the web user's search behavior. IR is the process of obtaining relevant information from a collection of informational resources. IR has considerably changed with the expansion of the Internet and the advent of modern and inexpensive graphical user interfaces and mass storage devices. The effective IR system, including an active indexing system, not only decreases the chances that information will be misfiled but also expedites the retrieval of information. Regarding IR utilization, the resulting time-saving benefit increases office efficiency and productivity while decreasing stress and anxiety. Most IR systems provide the advanced searching capabilities that allow users to create the sophisticated queries. The chapter argues that applying web mining and IR has the potential to enhance organizational performance and reach strategic goals in the digital age.

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.

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.

A general-purpose, interactive computerized information retrieval system specially suitable for the retrieval of bibliographic information from a small scale database. (DB) containing up to 15000 records is described. The user defines fields in terms of tags through the data definition processor which provides flexibility for the record structure. Another processor creates the DB from an off-line input file containing the tag(s) followed by the data for the field(s) supplied by the user. Retrieval of information is carried out by the query processor in an interactive manner. It provides options to (i) select a descriptor (the postings are displayed; (ii) combine 2 sets at a time; (iii) display the different sets chosen; and iv) print the chosen set(s) with full record details or specified tag fields only. The package is developed on an Usha-Alpha 1042 system using Alpha BASIC language under AMOS operating system.

For the user’s point of view, in large environments, it can be desirable to have Information Retrieval Systems (IRS) that retrieve documents according to their relevance levels. Relevance levels have been studied in some previous Information Retrieval (IR) works while some others (few) IR research works tackled the questions of IRS effectiveness and collections size. These latter works used standard IR measures on collections of increasing size to analyze IRS effectiveness scalability. In this work, we bring together these two issues in IR (multigraded relevance and scalability) by designing some new metrics for evaluating the ability of IRS to rank documents according to their relevance levels when collection size increases.

The dominant existing routing strategies employed in peer-to-peer(P2P) based information retrieval(IR) systems are similarity-based approaches. In these approaches, agents depend on the content similarity between incoming queries and their direct neighboring agents to direct the distributed search sessions. However, such a heuristic is myopic in that the neighboring agents may not be connected to more relevant agents. In this paper, an online reinforcement-learning based approach is developed to take advantage of the dynamic run-time characteristics of P2P IR systems as represented by information about past search sessions. Specifically, agents maintain estimates on the downstream agents' abilities to provide relevant documents for incoming queries. These estimates are updated gradually by learning from the feedback information returned from previous search sessions. Based on this information, the agents derive corresponding routing policies. Thereafter, these agents route the queries based on the learned policies and update the estimates based on the new routing policies. Experimental results demonstrate that the learning algorithm improves considerably the routing performance on two test collection sets that have been used in a variety of distributed IR studies.

The rapid advancement of information technology has brought significant transformation across multiple sectors, including library management systems. One of the pressing needs in higher education libraries is the development of an efficient, accurate, and secure borrowing system that reduces human error and improves service quality. This study aims to design and implement a book borrowing system for the STMIK Kaputama library by utilizing Radio Frequency Identification (RFID) technology integrated with the Internet of Things (IoT). The proposed system employs the ESP32 microcontroller as the core controller, supported by the RFID RC522 module and buzzer as primary devices to facilitate the automatic identification of library members and borrowed books. The borrowing and returning process is executed through RFID card scanning, with all transaction data transmitted via WiFi and stored in a MySQL database, which is managed through a PHP-based web platform. The development process follows the Agile methodology, enabling iterative improvement and adaptability to user requirements. System testing demonstrates that the integration of RFID and IoT technology significantly enhances the efficiency, accuracy, and speed of library operations compared to the previous manual system. Furthermore, the system allows real-time recording of borrowing transactions, monitoring of user activities, and centralized data management. These features not only streamline library services but also improve data security and reduce the risk of loss or duplication of records. Overall, the implementation of this RFID-IoT-based system provides an innovative solution for modernizing library management, particularly in higher education institutions. The system ensures faster services, minimizes errors, and creates a structured and reliable digital infrastructure to support academic information services. This study highlights the potential of combining RFID and IoT technologies to improve the quality and effectiveness of library systems in the digital era.

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.

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.

Cross language information retrieval (CLIR) is a retrieval process in which the user fires queries in one language to retrieve information from another (different) language. The diversity of information and language barriers are the serious issues for communication and cultural exchange across the world. To solve such barriers, Cross language information retrieval system, are nowadays in strong demand. CLIR is a subset of Information Retrieval (IR) system. Information Retrieval deals with finding useful information from a large collection of unstructured, structured and semi-structured data to a user query where the query is a set of keywords. Information Retrieval can be classified into different classes such as Monolingual information retrieval, Bi-Lingual Information Retrieval, Multilingual information retrieval and Cross language information retrieval. This paper focuses on the various IR variants and techniques used in CLIR system. Further, based on available literature, a number of challenges and issues in CLIR have been identified and discussed. It gives an overview of the advantages, limitations, tools available in CLIR research. It also describes new application areas of CLIR such as medical, multimedia, question answering system etc. The need for exploring and building more specialized information system that enable speakers of an Odia language to discover valuable information beyond linguistic and cultural barriers. This study is aimed at building an experimental CLIR system between one of the under-resourced language (i.e. Odia) and one of the most commonly used online language (i.e. English) in future.