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1.
[目的] 为了满足情报3.0时代用户对科技情报服务个性化与智能化的要求,采用用户画像方法挖掘科技情报用户情报需求与偏好。[方法] 以TAM理论的两个关键因素（感知有用性与易用性）为理论基础,通过挖掘科技情报用户行为日志数据以及问卷调查等方法深入挖掘科技情报用户在不同情境下的科技情报需求偏好以及搜索行为习惯,以专家访谈法为基础,基于VSM理论构建科技情报用户画像模型。[结果] 通过协同过滤算法对不同场景的科技情报用户进行服务推送。[结论] 运用标签云技术（Tagxedo技术）为处于不同场景的科技情报用户定制有针对性的个性化服务方案是情报3.0时代一种有效的智能化服务途径。 相似文献
2.
Daqing He Peter Brusilovsky Jaewook Ahn Jonathan Grady Rosta Farzan Yefei Peng Yiming Yang Monica Rogati 《Information processing & management》2008
Exploratory search increasingly becomes an important research topic. Our interests focus on task-based information exploration, a specific type of exploratory search performed by a range of professional users, such as intelligence analysts. In this paper, we present an evaluation framework designed specifically for assessing and comparing performance of innovative information access tools created to support the work of intelligence analysts in the context of task-based information exploration. The motivation for the development of this framework came from our needs for testing systems in task-based information exploration, which cannot be satisfied by existing frameworks. The new framework is closely tied with the kind of tasks that intelligence analysts perform: complex, dynamic, and multiple facets and multiple stages. It views the user rather than the information system as the center of the evaluation, and examines how well users are served by the systems in their tasks. The evaluation framework examines the support of the systems at users’ major information access stages, such as information foraging and sense-making. The framework is accompanied by a reference test collection that has 18 tasks scenarios and corresponding passage-level ground truth annotations. To demonstrate the usage of the framework and the reference test collection, we present a specific evaluation study on CAFÉ, an adaptive filtering engine designed for supporting task-based information exploration. This study is a successful use case of the framework, and the study indeed revealed various aspects of the information systems and their roles in supporting task-based information exploration. 相似文献
3.
In this paper, we present ViGOR (Video Grouping, Organisation and Recommendation), an exploratory video retrieval system. Exploratory video retrieval tasks are hampered by the lack of semantics associated to video and the overwhelming amount of video items stored in these types of collections (e.g. YouTube, MSN video, etc.). In order to help facilitate these exploratory video search tasks we present a system that utilises two complementary approaches: the first a new search paradigm that allows the semantic grouping of videos and the second the exploitation of past usage history in order to provide video recommendations. We present two types of recommendation techniques adapted to the grouping search paradigm: the first is a global recommendation, which couples the multi-faceted nature of explorative video retrieval tasks with the current user need of information in order to provide recommendations, and second is a local recommendation, which exploits the organisational features of ViGOR in order to provide more localised recommendations based on a specific aspect of the user task. Two user evaluations were carried out in order to (1) validate the new search paradigm provided by ViGOR, characterised by the grouping functionalities and (2) evaluate the usefulness of the proposed recommendation approaches when integrated into ViGOR. The results of our evaluations show (1) that the grouping, organisational and recommendation functionalities can result in an improvement in the users’ search performance without adversely impacting their perceptions of the system and (2) that both recommendation approaches are relevant to the users at different stages of their search, showing the importance of using multi-faceted recommendations for video retrieval systems and also illustrating the many uses of collaborative recommendations for exploratory video search tasks. 相似文献
4.
《Information processing & management》2016,52(1):61-72
In recent years, there has been a rapid growth of user-generated data in collaborative tagging (a.k.a. folksonomy-based) systems due to the prevailing of Web 2.0 communities. To effectively assist users to find their desired resources, it is critical to understand user behaviors and preferences. Tag-based profile techniques, which model users and resources by a vector of relevant tags, are widely employed in folksonomy-based systems. This is mainly because that personalized search and recommendations can be facilitated by measuring relevance between user profiles and resource profiles. However, conventional measurements neglect the sentiment aspect of user-generated tags. In fact, tags can be very emotional and subjective, as users usually express their perceptions and feelings about the resources by tags. Therefore, it is necessary to take sentiment relevance into account into measurements. In this paper, we present a novel generic framework SenticRank to incorporate various sentiment information to various sentiment-based information for personalized search by user profiles and resource profiles. In this framework, content-based sentiment ranking and collaborative sentiment ranking methods are proposed to obtain sentiment-based personalized ranking. To the best of our knowledge, this is the first work of integrating sentiment information to address the problem of the personalized tag-based search in collaborative tagging systems. Moreover, we compare the proposed sentiment-based personalized search with baselines in the experiments, the results of which have verified the effectiveness of the proposed framework. In addition, we study the influences by popular sentiment dictionaries, and SenticNet is the most prominent knowledge base to boost the performance of personalized search in folksonomy. 相似文献
5.
《Information processing & management》2001,37(3):435-458
We are interested in how ideas from document clustering can be used to improve the retrieval accuracy of ranked lists in interactive systems. In particular, we are interested in ways to evaluate the effectiveness of such systems to decide how they might best be constructed. In this study, we construct and evaluate systems that present the user with ranked lists and a visualization of inter-document similarities. We first carry out a user study to evaluate the clustering/ranked list combination on instance-oriented retrieval, the task of the TREC-6 Interactive Track. We find that although users generally prefer the combination, they are not able to use it to improve effectiveness. In the second half of this study, we develop and evaluate an approach that more directly combines the ranked list with information from inter-document similarities. Using the TREC collections and relevance judgments, we show that it is possible to realize substantial improvements in effectiveness by doing so, and that although users can use the combined information effectively, the system can provide hints that substantially improve on the user's solo effort. The resulting approach shares much in common with an interactive application of incremental relevance feedback. Throughout this study, we illustrate our work using two prototype systems constructed for these evaluations. The first, AspInQuery, is a classic information retrieval system augmented with a specialized tool for recording information about instances of relevance. The other system, Lighthouse, is a Web-based application that combines a ranked list with a portrayal of inter-document similarity. Lighthouse can work with collections such as TREC, as well as the results of Web search engines. 相似文献
6.
Lori Lorigo Bing Pan Helene Hembrooke Thorsten Joachims Laura Granka Geri Gay 《Information processing & management》2006
To improve search engine effectiveness, we have observed an increased interest in gathering additional feedback about users’ information needs that goes beyond the queries they type in. Adaptive search engines use explicit and implicit feedback indicators to model users or search tasks. In order to create appropriate models, it is essential to understand how users interact with search engines, including the determining factors of their actions. Using eye tracking, we extend this understanding by analyzing the sequences and patterns with which users evaluate query result returned to them when using Google. We find that the query result abstracts are viewed in the order of their ranking in only about one fifth of the cases, and only an average of about three abstracts per result page are viewed at all. We also compare search behavior variability with respect to different classes of users and different classes of search tasks to reveal whether user models or task models may be greater predictors of behavior. We discover that gender and task significantly influence different kinds of search behaviors discussed here. The results are suggestive of improvements to query-based search interface designs with respect to both their use of space and workflow. 相似文献
7.
8.
现代图书馆的信息服务是数字化的,用户是数字图书馆的中心和归宿。基于这一观点,笔者阐明了用户个性化信息需求的重要性和必需性;详细解释了基于微内容重组的信息交互服务、基于Agent技术的信息交互服务,以及图书馆2.0的信息交互服务;清晰阐明了用户需求个性化在交互式信息服务中的核心地位。 相似文献
9.
《Information processing & management》2023,60(2):103176
Modern information-seeking systems are becoming more interactive, mainly through asking Clarifying Questions (CQs) to refine users’ information needs. System-generated CQs may be of different qualities. However, the impact of asking multiple CQs of different qualities in a search session remains underexplored. Given the multi-turn nature of conversational information-seeking sessions, it is critical to understand and measure the impact of CQs of different qualities, when they are posed in various orders. In this paper, we conduct a user study on CQ quality trajectories, i.e., asking CQs of different qualities in chronological order. We aim to investigate to what extent the trajectory of CQs of different qualities affects user search behavior and satisfaction, on both query-level and session-level. Our user study is conducted with 89 participants as search engine users. Participants are asked to complete a set of Web search tasks. We find that the trajectory of CQs does affect the way users interact with Search Engine Result Pages (SERPs), e.g., a preceding high-quality CQ prompts the depth users to interact with SERPs, while a preceding low-quality CQ prevents such interaction. Our study also demonstrates that asking follow-up high-quality CQs improves the low search performance and user satisfaction caused by earlier low-quality CQs. In addition, only showing high-quality CQs while hiding other CQs receives better gains with less effort. That is, always showing all CQs may be risky and low-quality CQs do disturb users. Based on observations from our user study, we further propose a transformer-based model to predict which CQs to ask, to avoid disturbing users. In short, our study provides insights into the effects of trajectory of asking CQs, and our results will be helpful in designing more effective and enjoyable search clarification systems. 相似文献
10.
The evaluation of exploratory search relies on the ongoing paradigm shift from focusing on the search algorithm to focusing on the interactive process. This paper proposes a model-driven formative evaluation approach, in which the goal is not the evaluation of a specific system, per se, but the exploration of new design possibilities. This paper gives an example of this approach where a model of sensemaking was used to inform the evaluation of a basic exploratory search system(s) in the context of a sensemaking task. The model suggested that, rather than just looking at simple search performance measures, we should examine closely the interwoven, interactive processes of both representation construction and information seeking. Participants were asked to make sense of an unfamiliar topic using an augmented query-based search system. The processes of representation construction and information seeking were captured and analyzed using data from experiment notes, interviews, and a system log. The data analysis revealed users’ sources of ideas for structuring representations and a tightly coupled relationship between search and representation construction in their exploratory searches. For example, users strategically used search to find useful structure ideas instead of just accumulating information facts. Implications for improving current search systems and designing new systems are discussed. 相似文献
11.
《Information processing & management》2023,60(3):103300
Pre-adoption expectations often serve as an implicit reference point in users’ evaluation of information systems and are closely associated with their goals of interactions, behaviors, and overall satisfaction. Despite the empirically confirmed impacts, users’ search expectations and their connections to tasks, users, search experiences, and behaviors have been scarcely studied in the context of online information search. To address the gap, we collected 116 sessions from 60 participants in a controlled-lab Web search study and gathered direct feedback on their in-situ expected information gains (e.g., number of useful pages) and expected search efforts (e.g., clicks and dwell time) under each query during search sessions. Our study aims to examine (1) how users’ pre-search experience, task characteristics, and in-session experience affect their current expectations and (2) how user expectations are correlated with search behaviors and satisfaction. Our results with both quantitative and qualitative evidence demonstrate that: (1) user expectation is significantly affected by task characteristics, previous and in-situ search experience; (2) user expectation is closely associated with users’ browsing behaviors and search satisfaction. The knowledge learned about user expectation advances our understanding of users’ search behavioral patterns and their evaluations of interaction experience and will also facilitate the design, implementation, and evaluation of expectation-aware user models, metrics, and information retrieval (IR) systems. 相似文献
12.
Categorized overviews of web search results are a promising way to support user exploration, understanding, and discovery. These search interfaces combine a metadata-based overview with the list of search results to enable a rich form of interaction. A study of 24 sophisticated users carrying out complex tasks suggests how searchers may adapt their search tactics when using categorized overviews. This mixed methods study evaluated categorized overviews of web search results organized into thematic, geographic, and government categories. Participants conducted four exploratory searches during a 2-hour session to generate ideas for newspaper articles about specified topics such as “human smuggling.” Results showed that subjects explored deeper while feeling more organized, and that the categorized overview helped subjects better assess their results, although no significant differences were detected in the quality of the article ideas. A qualitative analysis of searcher comments identified seven tactics that participants reported adopting when using categorized overviews. This paper concludes by proposing a set of guidelines for the design of exploratory search interfaces. An understanding of the impact of categorized overviews on search tactics will be useful to web search researchers, search interface designers, information architects and web developers. 相似文献
13.
《Information processing & management》1999,35(2):121-139
It is well-known that relevance feedback is a method significant in improving the effectiveness of information retrieval systems. Improving effectiveness is important since these information retrieval systems must gain access to large document collections distributed over different distant sites. As a consequence, efforts to retrieve relevant documents have become significantly greater. Relevance feedback can be viewed as an aid to the information retrieval task. In this paper, a relevance feedback strategy is presented. The strategy is based on back-propagation of the relevance of retrieved documents using an algorithm developed in a neural approach. This paper describes a neural information retrieval model and emphasizes the results obtained with the associated relevance back-propagation algorithm in three different environments: manual ad hoc, automatic ad hoc and mixed ad hoc strategy (automatic plus manual ad hoc). 相似文献
14.
Considerable evidence exists to show that the use of term relevance weights is beneficial in interactive information retrieval. Various term weighting systems are reviewed. An experiment is then described in which information retrieval users are asked to rank query terms in decreasing order of presumed importance prior to actual search and retrieval. The experimental design is examined, and various relevance ranking systems are evaluated, including fully automatic systems based on inverse document frequency parameters, human rankings performed by the user population, and combinations of the two. 相似文献
15.
《Information processing & management》2016,52(6):1122-1141
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. 相似文献
16.
《Information processing & management》2002,38(3):401-426
A growing body of studies is developing approaches to evaluating human interaction with Web search engines, including the usability and effectiveness of Web search tools. This study explores a user-centered approach to the evaluation of the Web search engine Inquirus – a Web meta-search tool developed by researchers from the NEC Research Institute. The goal of the study reported in this paper was to develop a user-centered approach to the evaluation including: (1) effectiveness: based on the impact of users' interactions on their information problem and information seeking stage, and (2) usability: including screen layout and system capabilities for users. Twenty-two volunteers searched Inquirus on their own personal information topics. Data analyzed included: (1) user pre- and post-search questionnaires and (2) Inquirus search transaction logs. Key findings include: (1) Inquirus was rated highly by users on various usability measures, (2) all users experienced some level of shift/change in their information problem, information seeking, and personal knowledge due to their Inquirus interaction, (3) different users experienced different levels of change/shift, and (4) the search measure precision did not correlate with other user-based measures. Some users experienced major changes/shifts in various user-based variables, such as information problem or information seeking stage with a search of low precision and vice versa. Implications for the development of user-centered approaches to the evaluation of Web and information retrieval (IR) systems and further research are discussed. 相似文献
17.
本文在介绍用户体验概念的基础上,通过用户个体行为和群体行为分析,提出Web环境下的用户体验设计要注重个体行为体验和社群交互体验两方面,以个性化的信息空间和开放、共享的社群体验设计,不仅实现以用户为中心的、量身定制的用户体验,还要满足用户的社会化需求和自我价值的实现,这是超越传统个体行为体验的新形式。 相似文献
18.
[目的/意义] 随着智媒体技术的快速发展,越来越多的企业利用各种智媒体平台与用户进行信息交互,通过获取用户信息数据,分析用户信息行为了解用户需求,提升用户信息服务质量。[方法/过程] 本文以信息系统成功模型为基础,基于信息生态理论构建智媒体环境下企业与用户信息交互意愿的影响因素模型,通过问卷调查和结构方程进行实证研究以验证模型的有效性。[结果/结论] 数据结果表明,智媒体系统质量、信息质量、服务质量以及沉浸体验对用户满意度具有正向影响,且用户满意度正向影响信息交互行为。本研究可以帮助企业完善智媒体的交互功能,对企业智媒体平台健康发展起到一定的指导作用。 相似文献
19.
The concept of an “information space” provides a powerful metaphor for guiding the design of interactive retrieval systems. We present a case study of related article search, a browsing tool designed to help users navigate the information space defined by results of the PubMed® search engine. This feature leverages content-similarity links that tie MEDLINE® citations together in a vast document network. We examine the effectiveness of related article search from two perspectives: a topological analysis of networks generated from information needs represented in the TREC 2005 genomics track and a query log analysis of real PubMed users. Together, data suggest that related article search is a useful feature and that browsing related articles has become an integral part of how users interact with PubMed. 相似文献
20.
《Information processing & management》2019,56(5):1667-1679
In this paper, we explore the effects of individual pressure level and time constraint on searchers' behaviors and their assessment of search experience within the framework of interactive information retrieval. A user experiment was conducted in which 40 participants individually searched for information in a laboratory setting under two conditions: with time constraint (TC) and with no time constraint (NTC). Participants filled in a Perceived Stress Scale questionnaire to measure their chronic pressure value (subjective stress), and their pressure value was recorded as their individual characteristic. The results showed that the more chronic pressure the searcher has, the more search efforts they devote, including more time in searching and more time to complete the search tasks, especially when there was no time constraint. Time constraint and searchers’ pressure value had a significant effect on users’ numbers of scrolling actions per minute. The results indicate that when given a time constraint, searchers with higher-pressure values tend to lower their reading or scanning speed, while searchers with lower-pressure values tend to accelerate their reading or scanning speed. The results suggested different people would react to the time condition change in different ways, especially people with higher pressure. Therefore, it is necessary to examine users’ search behaviors in person-in-situation frameworks to analyze the effects of contextual factors on users. This study contributes to our knowledge of how contextual factors and individual characteristics affect searchers’ behaviors and have implications for the design of IIR systems. 相似文献