The impact of text browsing on text retrieval performance

The results from a series of three experiments that used Text Retrieval Conference (TREC) data and TREC search topics are compared. These experiments each involved three novel user interfaces (one per experiment). User interfaces that made it easier for users to view text were found to improve recall in all three experiments. A distinction was found between a cluster of subjects (a majority of whom were search experts) who tended to read fewer documents more carefully (readers, or exclusives) and subjects who skimmed through more documents without reading them as carefully (skimmers, or inclusives). Skimmers were found to have significantly better recall overall. A major outcome from our experiments at TREC and with the TREC data, is that hypertext interfaces to information retrieval (IR) tasks tend to increase recall. Our interpretation of this pattern of results across the three experiments is that increased interaction with the text (more pages viewed) generally improves recall. Findings from one of the experiments indicated that viewing a greater diversity of text on a single screen (i.e., not just more text per se, but more articles available at once) may also improve recall. In an experiment where a traditional (type-in) query interface was contrasted with a condition where queries were marked up on the text, the improvement in recall due to viewing more text was more pronounced with search novices. Our results demonstrate that markup and hypertext interfaces to text retrieval systems can benefit recall and can also benefit novices. The challenge now will be to find modified versions of hypertext interfaces that can improve precision, as well as recall and that can work with users who prefer to use different types of search strategy or have different types of training and experience.     

Mix and match: combining terms and operators for successful Web searches

This paper presents a detailed analysis of the structure and components of queries written by experimental participants in a study that manipulated two factors found to affect end-user information retrieval performance: training in Boolean logic and the type of search interface. As reported previously, we found that both Boolean training and the use of an assisted interface improved the participants' ability to find correct responses to information requests. Here, we examine the impact of these training and interface manipulations on the Boolean operators and search terms that comprise the submitted queries. Our analysis shows that both Boolean training and the use of an assisted interface improved the participants' ability to correctly utilize various operators. An unexpected finding is that this training also had a positive impact on term selection. The terms and, to a lesser extent, the operators comprising a query were important factors affecting the participants' performance in query tasks. Our findings demonstrate that even small training interventions can improve the users' search performance and highlight the need for additional information retrieval research into how search interfaces can provide superior support to today's untrained users of the Web.     

Automatic query formulations in information retrieval.

Modern information retrieval systems are designed to supply relevant information in response to requests received from the user population. In most retrieval environments the search requests consist of keywords, or index terms, interrelated by appropriate Boolean operators. Since it is difficult for untrained users to generate effective Boolean search requests, trained search intermediaries are normally used to translate original statements of user need into useful Boolean search formulations. Methods are introduced in this study which reduce the role of the search intermediaries by making it possible to generate Boolean search formulations completely automatically from natural language statements provided by the system patrons. Frequency considerations are used automatically to generate appropriate term combinations as well as Boolean connectives relating the terms. Methods are covered to produce automatic query formulations both in a standard Boolean logic system, as well as in an extended Boolean system in which the strict interpretation of the connectives is relaxed. Experimental results are supplied to evaluate the effectiveness of the automatic query formulation process, and methods are described for applying the automatic query formulation process in practice.     

User evaluation of automatically generated semantic hypertext links in a heavily used procedural manual

This paper is an interim report on our efforts at NIST to construct an information discovery tool through the fusion of hypertext and information retrieval (IR) technologies. The tool works by parsing a contiguous document base into smaller documents and inserting semantic links between these documents using document–document similarity measures based on IR techniques. The focus of the paper is a case study in which domain experts evaluate the utility of the tool in the performance of information discovery tasks on a large, dynamic procedural manual. The results of the case study are discussed, and their implications for the design of large-scale automatic hypertext generation systems are described.     

A comparison of two methods for boolean query relevancy feedback†

The relevance feedback process uses information derived from an initially retrieved set of documents to improve subsequent search formulations and retrieval output. In a Boolean query environment this implies that new query terms must be identified and Boolean operators must be chosen automatically to connect the various query terms. In this study two recently proposed automatic methods for relevance feedback of Boolean queries are evaluated and conclusions are drawn concerning the use of effective feedback methods in a Boolean query environment.     

布尔逻辑检索和自然语言检索对比研究

采用4种检索方式（无过滤布尔逻辑、过滤布尔逻辑、无过滤自然语言和过滤自然语言）对7个常见数据库ASP、GS、JSTOR、LexisNexis、ProQuest Central、PubMed、Scopus和Web of Science检索测试,最后分析了在目前技术环境下,布尔逻辑和自然语言检索相比,哪种方式更加有效。     

Challenging conventional assumptions of automated information retrieval with real users: Boolean searching and batch retrieval evaluations

Two common assumptions held by information retrieval researchers are that searching using Boolean operators is inferior to natural language searching and that results from batch-style retrieval evaluations are generalizable to the real-world searching. We challenged these assumptions in the Text Retrieval Conference (TREC) interactive track, with real users following a consensus protocol to search for an instance recall task. Our results showed that Boolean and natural language searching achieved comparable results and that the results from batch evaluations were not comparable to those obtained in experiments with real users.     

Supporting exploratory video retrieval tasks with grouping and recommendation

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.     

Inter and intra-document contexts applied in polyrepresentation for best match IR

The principle of polyrepresentation offers a theoretical framework for handling multiple contexts in information retrieval (IR). This paper presents an empirical laboratory study of polyrepresentation in restricted mode of the information space with focus on inter and intra-document features. The Cystic Fibrosis test collection indexed in the best match system InQuery constitutes the experimental setting. Overlaps between five functionally and/or cognitively different document representations are identified. Supporting the principle of polyrepresentation, results show that in general overlaps generated by three or four representations of different nature have higher precision than those generated from two representations or the single fields. This result pertains to both structured and unstructured query mode in best match retrieval, however, with the latter query mode demonstrating higher performance. The retrieval overlaps containing search keys from the bibliographic references provide the best retrieval performance and minor MeSH terms the worst. It is concluded that a highly structured query language is necessary when implementing the principle of polyrepresentation in a best match IR system because the principle is inherently Boolean. Finally a re-ranking test shows promising results when search results are re-ranked according to precision obtained in the overlaps whilst re-ranking by citations seems less useful when integrated into polyrepresentative applications.     

Adaptive visualization for exploratory information retrieval

As the volume and breadth of online information is rapidly increasing, ad hoc search systems become less and less efficient to answer information needs of modern users. To support the growing complexity of search tasks, researchers in the field of information developed and explored a range of approaches that extend the traditional ad hoc retrieval paradigm. Among these approaches, personalized search systems and exploratory search systems attracted many followers. Personalized search explored the power of artificial intelligence techniques to provide tailored search results according to different user interests, contexts, and tasks. In contrast, exploratory search capitalized on the power of human intelligence by providing users with more powerful interfaces to support the search process. As these approaches are not contradictory, we believe that they can re-enforce each other. We argue that the effectiveness of personalized search systems may be increased by allowing users to interact with the system and learn/investigate the problem in order to reach the final goal. We also suggest that an interactive visualization approach could offer a good ground to combine the strong sides of personalized and exploratory search approaches. This paper proposes a specific way to integrate interactive visualization and personalized search and introduces an adaptive visualization based search system Adaptive VIBE that implements it. We tested the effectiveness of Adaptive VIBE and investigated its strengths and weaknesses by conducting a full-scale user study. The results show that Adaptive VIBE can improve the precision and the productivity of the personalized search system while helping users to discover more diverse sets of information.     

Adaptive relevance feedback method of extended Boolean model using hierarchical clustering techniques

The relevance feedback process uses information obtained from a user about a set of initially retrieved documents to improve subsequent search formulations and retrieval performance. In extended Boolean models, the relevance feedback implies not only that new query terms must be identified and re-weighted, but also that the terms must be connected with Boolean And/Or operators properly. Salton et al. proposed a relevance feedback method, called DNF (disjunctive normal form) method, for a well established extended Boolean model. However, this method mainly focuses on generating Boolean queries but does not concern about re-weighting query terms. Also, this method has some problems in generating reformulated Boolean queries. In this study, we investigate the problems of the DNF method and propose a relevance feedback method using hierarchical clustering techniques to solve those problems. We also propose a neural network model in which the term weights used in extended Boolean queries can be adjusted by the users’ relevance feedbacks.     

Searching the Web: operator assistance required

This study examines the effects of the search interface and Boolean logic training on user search performance and satisfaction. We compared the use of an assisted search tool to that of a simple search interface like those typically found at commercial search engine sites. We found that the assisted search tool had a significant positive effect on performance, satisfaction, and confidence. Promoting the use of advanced search features is therefore in the best interest of both Web search providers and users. In the absence of an assisted interface, a simple interface coupled with Boolean logic training was also an effective means for improving user performance. Given that most searchers choose to use the simple search box, it is important to provide them with applicable training to promote the effective use of the search tool. Interestingly, coupling the assisted interface with Boolean training was no more effective than either treatment alone.     

Examining users’ knowledge change in the task completion process

This paper examines the changes of information searchers’ topic knowledge levels in the process of completing information tasks. Multi-session tasks were used in the study, which enables the convenience of eliciting users’ topic knowledge during their process of completing the whole tasks. The study was a 3-session laboratory experiment with 24 participants, each time working on one subtask in an assigned 3-session general task. The general task was either parallel or dependently structured. Questionnaires were administered before and after each session to elicit users’ perceptions of their knowledge levels, task attributes, and other task features, for both the overall task and the sub-tasks. Our results support the assumption that users’ knowledge generally increases after each search session, but there were exceptions in which a “ceiling” effect was shown. We also found that knowledge was correlated with users’ perceptions of task attributes and accomplishment. In addition, task type was found to affect several aspects of knowledge levels and knowledge change. These findings further our understanding of users’ knowledge in information tasks and are thus helpful for information retrieval research and system design.     

基于实验研究的儿童搜索引擎设计

[目的/意义]针对目前儿童搜索引擎在搜索过程中对儿童认知和情感引导上的缺乏,提出了一个符合儿童认知、情感和感官需求的具有社交化智能的儿童搜索引擎设计方法,为儿童搜索引擎设计和研发提供思路和方向。[方法/过程]使用百度搜索引擎进行儿童信息检索实验,根据儿童在完成3种类型实验任务时的认知、情感表现,结合儿童教育与发展理论,分析了认知、情感和感官要素对儿童检索过程和结果的影响,并以此为依据,从认知、情感和感官3个维度进行儿童搜索引擎设计。[结果/结论]为能更顺利地完成信息检索任务,儿童需要具有认知引导与共情功能的搜索引擎辅助检索活动进行,帮助他们在检索中获得知识、提升技能。     

Trends in subject heading assignment in cataloging records during 1974–1978

The cataloging records for monographs and reports produced during 1974 and 1978 in the National Union Catalog and Government Reports Announcements were analysed and the characteristics of subject heading assignments determined. The study indicates that the assignment of subject headings is correlated not only with time, but with discipline, and document type also. The average rate of assignment during the period has been more than two. The study indicates the feasibility of developing “Boolean logic” based computerized retrieval systems for subject search. It also indicates growth of cataloging records in the subject files in the coming years for monographs in physical sciences and in engineering and technology.     

A mathematical model of a weighted boolean retrieval system

The use of weights to denote a query representation and/or the indexing of a document is analysed as a generalization of a Boolean retrieval system. Criteria are given for the functions used to evaluate the relevance of the records to a specific query, including self-consistency. Various mechanisms suggested in the literature for evaluating the relevance of records with regard to a given query are tested and found to be less than satisfactory. A new approach is suggested to avoid some of the perils of a weighted Boolean retrieval system.     

Multi-facet product information search and retrieval using semantically annotated product family ontology

With the advent of various services and applications of Semantic Web, semantic annotation has emerged as an important research topic. The application of semantically annotated ontology had been evident in numerous information processing and retrieval tasks. One of such tasks is utilizing the semantically annotated ontology in product design which is able to suggest many important applications that are critical to aid various design related tasks. However, ontology development in design engineering remains a time consuming and tedious task that demands considerable human efforts. In the context of product family design, management of different product information that features efficient indexing, update, navigation, search and retrieval across product families is both desirable and challenging. For instance, an efficient way of retrieving timely information on product family can be useful for tasks such as product family redesign and new product variant derivation when requirements change. However, the current research and application of information search and navigation in product family is mostly limited to its structural aspect which is insufficient to handle advanced information search especially when the query targets at multiple aspects of a product. This paper attempts to address this problem by proposing an information search and retrieval framework based on the semantically annotated multi-facet product family ontology. Particularly, we propose a document profile (DP) model to suggest semantic tags for annotation purpose. Using a case study of digital camera families, we illustrate how the faceted search and retrieval of product information can be accomplished. We also exemplify how we can derive new product variants based on the designer’s query of requirements via the faceted search and retrieval of product family information. Lastly, in order to highlight the value of our current work, we briefly discuss some further research and applications in design decision support, e.g. commonality analysis and variety comparison, based on the semantically annotated multi-facet product family ontology.     

An associative search strategy for information retrieval

This paper extends Goffman's Indirect Method of Information Retrieval by suggesting a more flexible search strategy. The suggested strategy in its simplified version is more effective than the Boolean strategy used in existing information retrieval systems and can be implemented at comparable costs. Some of its features might further increase the effectiveness of information retrieval systems.