Search (76 results, page 1 of 4)

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Date

22. 2.2003 17:25:39
22. 2.2003 18:17:40

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a

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Abstract

A new search paradigm, in which the primary user activity is the guided exploration of a complex information space rather than the retrieval of items based on precise specifications, is proposed. The author claims that this paradigm is the norm in most practical applications, and that solutions based on traditional search methods are not effective in this context. He then presents a solution based on dynamic taxonomies, a knowledge management model that effectively guides users to reach their goal while giving them total freedom in exploring the information base. Applications, benefits, and current research are discussed.

Date

22. 7.2006 17:56:22

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Abstract

The digital library system Daffodil is targeted at strategic support of users during the information search process. For searching, exploring and managing digital library objects it provides user-customisable information seeking patterns over a federation of heterogeneous digital libraries. In this paper evaluation results with respect to retrieval effectiveness, efficiency and user satisfaction are presented. The analysis focuses on strategic support for the scientific work-flow. Daffodil supports the whole work-flow, from data source selection over information seeking to the representation, organisation and reuse of information. By embedding high level search functionality into the scientific work-flow, the user experiences better strategic system support due to a more systematic work process. These ideas have been implemented in Daffodil followed by a qualitative evaluation. The evaluation has been conducted with 28 participants, ranging from information seeking novices to experts. The results are promising, as they support the chosen model.

Date

16.11.2008 16:22:48

Type

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a

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Abstract

Humans can make hasty, but generally robust judgements about what a text fragment is, or is not, about. Such judgements are termed information inference. This article furnishes an account of information inference from a psychologistic stance. By drawing an theories from nonclassical logic and applied cognition, an information inference mechanism is proposed that makes inferences via computations of information flow through an approximation of a conceptual space. Within a conceptual space information is represented geometrically. In this article, geometric representations of words are realized as vectors in a high dimensional semantic space, which is automatically constructed from a text corpus. Two approaches were presented for priming vector representations according to context. The first approach uses a concept combination heuristic to adjust the vector representation of a concept in the light of the representation of another concept. The second approach computes a prototypical concept an the basis of exemplar trace texts and moves it in the dimensional space according to the context. Information inference is evaluated by measuring the effectiveness of query models derived by information flow computations. Results show that information flow contributes significantly to query model effectiveness, particularly with respect to precision. Moreover, retrieval effectiveness compares favorably with two probabilistic query models, and another based an semantic association. More generally, this article can be seen as a contribution towards realizing operational systems that mimic text-based human reasoning.

Date

22. 3.2003 19:35:46

Type

a

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Abstract

The study reported here investigated the query expansion behavior of end-users interacting with a thesaurus-enhanced search system on the Web. Two groups, namely academic staff and postgraduate students, were recruited into this study. Data were collected from 90 searches performed by 30 users using the OVID interface to the CAB abstracts database. Data-gathering techniques included questionnaires, screen capturing software, and interviews. The results presented here relate to issues of search-topic and search-term characteristics, number and types of expanded queries, usefulness of thesaurus terms, and behavioral differences between academic staff and postgraduate students in their interaction. The key conclusions drawn were that (a) academic staff chose more narrow and synonymous terms than did postgraduate students, who generally selected broader and related terms; (b) topic complexity affected users' interaction with the thesaurus in that complex topics required more query expansion and search term selection; (c) users' prior topic-search experience appeared to have a significant effect on their selection and evaluation of thesaurus terms; (d) in 50% of the searches where additional terms were suggested from the thesaurus, users stated that they had not been aware of the terms at the beginning of the search; this observation was particularly noticeable in the case of postgraduate students.

Date

22. 7.2006 16:32:43

Type

a

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Abstract

This paper addresses the problem of information discovery in large collections of text. For users, one of the key problems in working with such collections is determining where to focus their attention. In selecting documents for examination, users must be able to formulate reasonably precise queries. Queries that are too broad will greatly reduce the efficiency of information discovery efforts by overwhelming the users with peripheral information. In order to formulate efficient queries, a mechanism is needed to automatically alert users regarding potentially interesting information contained within the collection. This paper presents the results of an experiment designed to test one approach to generation of such alerts. The technique of latent semantic indexing (LSI) is used to identify relationships among entities of interest. Entity extraction software is used to pre-process the text of the collection so that the LSI space contains representation vectors for named entities in addition to those for individual terms. In the LSI space, the cosine of the angle between the representation vectors for two entities captures important information regarding the degree of association of those two entities. For appropriate choices of entities, determining the entity pairs with the highest mutual cosine values yields valuable information regarding the contents of the text collection. The test database used for the experiment consists of 150,000 news articles. The proposed approach for alert generation is tested using a counterterrorism analysis example. The approach is shown to have significant potential for aiding users in rapidly focusing on information of potential importance in large text collections. The approach also has value in identifying possible use of aliases.

Source

Proceedings of the Fourth Workshop on Link Analysis, Counterterrorism, and Security, SIAM Data Mining Conference, Bethesda, MD, 20-22 April, 2006. [http://www.siam.org/meetings/sdm06/workproceed/Link%20Analysis/15.pdf]

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Abstract

The Web provides a massive knowledge source, as do intranets and other electronic document collections. However, much of that knowledge is encoded implicitly and cannot be applied directly without processing into some more appropriate structures. Searching, browsing, question answering, for example, could all benefit from domain-specific knowledge contained in the documents, and in applications such as simple search we do not actually need very "deep" knowledge structures such as ontologies, but we can get a long way with a model of the domain that consists of term hierarchies. We combine domain knowledge automatically acquired by exploiting the documents' markup structure with knowledge extracted an the fly to assist a user with ad hoc search requests. Such a search system can suggest query modification options derived from the actual data and thus guide a user through the space of documents. This article gives a detailed account of a task-based evaluation that compares a search system that uses the outlined domain knowledge with a standard search system. We found that users do use the query modification suggestions proposed by the system. The main conclusion we can draw from this evaluation, however, is that users prefer a system that can suggest query modifications over a standard search engine, which simply presents a ranked list of documents. Most interestingly, we observe this user preference despite the fact that the baseline system even performs slightly better under certain criteria.

Type

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Abstract

Introducing context to a user query is effective to improve the search effectiveness. In this article we propose a method employing the taxonomy-based search services such as Web directories to facilitate searches in any Web search interfaces that support Boolean queries. The proposed method enables one to convey current search context an taxonomy of a taxonomy-based search service to the searches conducted with the Web search interfaces. The basic idea is to learn the search context in the form of a Boolean condition that is commonly accepted by many Web search interfaces, and to use the condition to modify the user query before forwarding it to the Web search interfaces. To guarantee that the modified query can always be processed by the Web search interfaces and to make the method adaptive to different user requirements an search result effectiveness, we have developed new fast classification learning algorithms.

Type

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Abstract

Semantic Search has become an active research of Semantic Web in recent years. The classification methodology plays a pretty critical role in the beginning of search process to disambiguate irrelevant information. However, the applications related to Folksonomy suffer from many obstacles. This study attempts to eliminate the problems resulted from Folksonomy using existing semantic technology. We also focus on how to effectively integrate heterogeneous ontologies over the Internet to acquire the integrity of domain knowledge. A faceted logic layer is abstracted in order to strengthen category framework and organize existing available ontologies according to a series of steps based on the methodology of faceted classification and ontology construction. The result showed that our approach can facilitate the integration of inconsistent or even heterogeneous ontologies. This paper also generalizes the principles of picking appropriate facets with which our facet browser completely complies so that better semantic search result can be obtained.

Type

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Abstract

The Medical professionals and researchers need information from reputable sources to accomplish their work. Unfortunately, the Web has a large number of documents that are irrelevant to their work, even those documents that purport to be "medically-related." This paper describes an architecture designed to integrate advanced searching and indexing algorithms, an automatic thesaurus, or "concept space," and Kohonen-based Self-Organizing Map (SOM) technologies to provide searchers with finegrained results. Initial results indicate that these systems provide complementary retrieval functionalities. HelpfulMed not only allows users to search Web pages and other online databases, but also allows them to build searches through the use of an automatic thesaurus and browse a graphical display of medical-related topics. Evaluation results for each of the different components are included. Our spidering algorithm outperformed both breadth-first search and PageRank spiders an a test collection of 100,000 Web pages. The automatically generated thesaurus performed as well as both MeSH and UMLS-systems which require human mediation for currency. Lastly, a variant of the Kohonen SOM was comparable to MeSH terms in perceived cluster precision and significantly better at perceived cluster recall.

Footnote

Teil eines Themenheftes: "Web retrieval and mining: A machine learning perspective"

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Abstract

This paper discusses issues concerning the augmentation of thesaurus relationships, in light of new application possibilities for retrieval. We first discuss a case study that explored the retrieval potential of an augmented set of thesaurus relationships by specialising standard relationships into richer subtypes, in particular hierarchical geographical containment and the associative relationship. We then locate this work in a broader context by reviewing various attempts to build taxonomies of thesaurus relationships, and conclude by discussing the feasibility of hierarchically augmenting the core set of thesaurus relationships, particularly the associative relationship. We discuss the possibility of enriching the specification and semantics of Related Term (RT relationships), while maintaining compatibility with traditional thesauri via a limited hierarchical extension of the associative (and hierarchical) relationships. This would be facilitated by distinguishing the type of term from the (sub)type of relationship and explicitly specifying semantic categories for terms following a faceted approach. We first illustrate how hierarchical spatial relationships can be used to provide more flexible retrieval for queries incorporating place names in applications employing online gazetteers and geographical thesauri. We then employ a set of experimental scenarios to investigate key issues affecting use of the associative (RT) thesaurus relationships in semantic distance measures. Previous work has noted the potential of RTs in thesaurus search aids but also the problem of uncontrolled expansion of query term sets. Results presented in this paper suggest the potential for taking account of the hierarchical context of an RT link and specialisations of the RT relationship

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Footnote

Rez. in: JASIST 54(2003) no.7, S.695-697 (R. Savolainen): "Donald O. Case has written an ambitious book to create an overall picture of the major approaches to information needs and seeking (INS) studies. The aim to write an extensive review is reflected in the list of references containing about 700 items. The high ambitions are explained an p. 14, where Case states that he is aiming at a multidisciplinary understanding of the concept of information seeking. In the Preface, the author characterizes his book as an introduction to the topic for students at the graduate level, as well as as a review and handbook for scholars engagged in information behavior research. In my view, Looking for Information is particularly welcome as an academic textbook because the field of INS studies suffers from the lack of monographs. Along with the continuous growth of the number of journal articles and conference papers, there is a genuine need for a book that picks up the numerous pieces and puts them together. The use of the study as a textbook is facilitated by clearly delineated sections an major themes and the wealth of concrete examples of information seeking in everyday contexts. The book is lucidly written and it is accessible to novice readers, too. At first glance, the idea of providing a comprehensive review of INS studies may seem a mission impossible because the current number of articles, papers, and other contributions in this field is nearing the 10,000 range (p. 224). Donald Case is not alone in the task of coming to grips with an increasing number of studies; similar problems have been faced by those writing INS-related chapters for the Annual Review of Information Science and Technology (ARIST). Case has solved the problem of "too many publications to be reviewed" by concentrating an the INS literature published during the last two decades. Secondly, studies an library use and information retrieval are discussed only to a limited extent. In addition, Case is highly selective as to studies focusing an the use of specific sources and channels such as WWW. These delineations are reasonable, even though they beg some questions. First, how should one draw the line between studies an information seeking and information retrieval? Case does not discuss this question in greater detail, although in recent years, the overlapping areas of information seeking and retrieval studies have been broadened, along with the growing importance of WWW in information seeking/retrieval. Secondly, how can one define the concept of information searching (or, more specifically, Internet or Web searching) in relation to information seeking and information retrieval? In the field of Web searching studies, there is an increasing number of contributions that are of direct relevance to information-seeking studies. Clearly, the advent of the Internet, particularly, the Web, has blurred the previous lines between INS and IR literature, making them less clear cut. The book consists of five main sections, and comprises 13 chapters. There is an Appendix serving the needs of an INS textbook (questions for discussion and application). The structure of the book is meticulously planned and, as a whole, it offers a sufficiently balanced contribution to theoretical, methodological, and empirical issues of INS. The title, Looking for Information: A Survey of Research an Information Seeking, Needs, and Behavior aptly describes the main substance of the book. . . . It is easy to agree with Case about the significance of the problem of specialization and fragmentation. This problem seems to be concomitant with the broadening field of INS research. In itself, Case's book can be interpreted as a struggle against this fragmentation. His book suggests that this struggle is not hopeless and that it is still possible to draw an overall picture of the evolving research field. The major pieces of the puzzle were found and the book will provide a useful overview of INS studies for many years."
Weitere Rez. in: iwp 65(2014) H.2, S.143-144 (C. Wolff)

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Abstract

In this article we present a method for retrieving documents from a digital library through a visual interface based on automatically generated concepts. We used a vocabulary generation algorithm to generate a set of concepts for the digital library and a technique called the max-min distance technique to cluster them. Additionally, the concepts were visualized in a spring embedding graph layout to depict the semantic relationship among them. The resulting graph layout serves as an aid to users for retrieving documents. An online archive containing the contents of D-Lib Magazine from July 1995 to May 2002 was used to test the utility of an implemented retrieval and visualization system. We believe that the method developed and tested can be applied to many different domains to help users get a better understanding of online document collections and to minimize users' cognitive load during execution of search tasks. Over the past few years, the volume of information available through the World Wide Web has been expanding exponentially. Never has so much information been so readily available and shared among so many people. Unfortunately, the unstructured nature and huge volume of information accessible over networks have made it hard for users to sift through and find relevant information. To deal with this problem, information retrieval (IR) techniques have gained more intensive attention from both industrial and academic researchers. Numerous IR techniques have been developed to help deal with the information overload problem. These techniques concentrate on mathematical models and algorithms for retrieval. Popular IR models such as the Boolean model, the vector-space model, the probabilistic model and their variants are well established.
From the user's perspective, however, it is still difficult to use current information retrieval systems. Users frequently have problems expressing their information needs and translating those needs into queries. This is partly due to the fact that information needs cannot be expressed appropriately in systems terms. It is not unusual for users to input search terms that are different from the index terms information systems use. Various methods have been proposed to help users choose search terms and articulate queries. One widely used approach is to incorporate into the information system a thesaurus-like component that represents both the important concepts in a particular subject area and the semantic relationships among those concepts. Unfortunately, the development and use of thesauri is not without its own problems. The thesaurus employed in a specific information system has often been developed for a general subject area and needs significant enhancement to be tailored to the information system where it is to be used. This thesaurus development process, if done manually, is both time consuming and labor intensive. Usage of a thesaurus in searching is complex and may raise barriers for the user. For illustration purposes, let us consider two scenarios of thesaurus usage. In the first scenario the user inputs a search term and the thesaurus then displays a matching set of related terms. Without an overview of the thesaurus - and without the ability to see the matching terms in the context of other terms - it may be difficult to assess the quality of the related terms in order to select the correct term. In the second scenario the user browses the whole thesaurus, which is organized as in an alphabetically ordered list. The problem with this approach is that the list may be long, and neither does it show users the global semantic relationship among all the listed terms.
Nevertheless, because thesaurus use has shown to improve retrieval, for our method we integrate functions in the search interface that permit users to explore built-in search vocabularies to improve retrieval from digital libraries. Our method automatically generates the terms and their semantic relationships representing relevant topics covered in a digital library. We call these generated terms the "concepts", and the generated terms and their semantic relationships we call the "concept space". Additionally, we used a visualization technique to display the concept space and allow users to interact with this space. The automatically generated term set is considered to be more representative of subject area in a corpus than an "externally" imposed thesaurus, and our method has the potential of saving a significant amount of time and labor for those who have been manually creating thesauri as well. Information visualization is an emerging discipline and developed very quickly in the last decade. With growing volumes of documents and associated complexities, information visualization has become increasingly important. Researchers have found information visualization to be an effective way to use and understand information while minimizing a user's cognitive load. Our work was based on an algorithmic approach of concept discovery and association. Concepts are discovered using an algorithm based on an automated thesaurus generation procedure. Subsequently, similarities among terms are computed using the cosine measure, and the associations among terms are established using a method known as max-min distance clustering. The concept space is then visualized in a spring embedding graph, which roughly shows the semantic relationships among concepts in a 2-D visual representation. The semantic space of the visualization is used as a medium for users to retrieve the desired documents. In the remainder of this article, we present our algorithmic approach of concept generation and clustering, followed by description of the visualization technique and interactive interface. The paper ends with key conclusions and discussions on future work.

Content

The JAVA applet is available at <http://ella.slis.indiana.edu/~junzhang/dlib/IV.html>. A prototype of this interface has been developed and is available at <http://ella.slis.indiana.edu/~junzhang/dlib/IV.html>. The D-Lib search interface is available at <http://www.dlib.org/Architext/AT-dlib2query.html>.

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Abstract

The Turn analyzes the research of information seeking and retrieval (IS&R) and proposes a new direction of integrating research in these two areas: the fields should turn off their separate and narrow paths and construct a new avenue of research. An essential direction for this avenue is context as given in the subtitle Integration of Information Seeking and Retrieval in Context. Other essential themes in the book include: IS&R research models, frameworks and theories; search and works tasks and situations in context; interaction between humans and machines; information acquisition, relevance and information use; research design and methodology based on a structured set of explicit variables - all set into the holistic cognitive approach. The present monograph invites the reader into a construction project - there is much research to do for a contextual understanding of IS&R. The Turn represents a wide-ranging perspective of IS&R by providing a novel unique research framework, covering both individual and social aspects of information behavior, including the generation, searching, retrieval and use of information. Regarding traditional laboratory information retrieval research, the monograph proposes the extension of research toward actors, search and work tasks, IR interaction and utility of information. Regarding traditional information seeking research, it proposes the extension toward information access technology and work task contexts. The Turn is the first synthesis of research in the broad area of IS&R ranging from systems oriented laboratory IR research to social science oriented information seeking studies. TOC:Introduction.- The Cognitive Framework for Information.- The Development of Information Seeking Research.- Systems-Oriented Information Retrieval.- Cognitive and User-Oriented Information Retrieval.- The Integrated IS&R Research Framework.- Implications of the Cognitive Framework for IS&R.- Towards a Research Program.- Conclusion.- Definitions.- References.- Index.

Footnote

Rez. in: Mitt. VÖB 59(2006) H.2, S.81-83 (O. Oberhauser): "Mit diesem Band haben zwei herausragende Vertreter der europäischen Informationswissenschaft, die Professoren Peter Ingwersen (Kopenhagen) und Kalervo Järvelin (Tampere) ein Werk vorgelegt, das man vielleicht dereinst als ihr opus magnum bezeichnen wird. Mich würde dies nicht überraschen, denn die Autoren unternehmen hier den ambitionierten Versuch, zwei informations wissenschaftliche Forschungstraditionen, die einander bisher in eher geringem Ausmass begegneten, unter einem gesamtheitlichen kognitiven Ansatz zu vereinen - das primär im sozialwissenschaftlichen Bereich verankerte Forschungsgebiet "Information Seeking and Retrieval" (IS&R) und das vorwiegend im Informatikbereich angesiedelte "Information Retrieval" (IR). Dabei geht es ihnen auch darum, den seit etlichen Jahren zwar dominierenden, aber auch als zu individualistisch kritisierten kognitiven Ansatz so zu erweitern, dass technologische, verhaltensbezogene und kooperative Aspekte in kohärenter Weise berücksichtigt werden. Dies geschieht auf folgende Weise in neun Kapiteln: - Zunächst werden die beiden "Lager" - die an Systemen und Laborexperimenten orientierte IR-Tradition und die an Benutzerfragen orientierte IS&R-Fraktion - einander gegenübergestellt und einige zentrale Begriffe geklärt. - Im zweiten Kapitel erfolgt eine ausführliche Darstellung der kognitiven Richtung der Informationswissenschaft, insbesondere hinsichtlich des Informationsbegriffes. - Daran schliesst sich ein Überblick über die bisherige Forschung zu "Information Seeking" (IS) - eine äusserst brauchbare Einführung in die Forschungsfragen und Modelle, die Forschungsmethodik sowie die in diesem Bereich offenen Fragen, z.B. die aufgrund der einseitigen Ausrichtung des Blickwinkels auf den Benutzer mangelnde Betrachtung der Benutzer-System-Interaktion. - In analoger Weise wird im vierten Kapitel die systemorientierte IRForschung in einem konzentrierten Überblick vorgestellt, in dem es sowohl um das "Labormodell" als auch Ansätze wie die Verarbeitung natürlicher Sprache und Expertensysteme geht. Aspekte wie Relevanz, Anfragemodifikation und Performanzmessung werden ebenso angesprochen wie die Methodik - von den ersten Laborexperimenten bis zu TREC und darüber hinaus.
- Kapitel fünf enthält einen entsprechenden Überblick über die kognitive und benutzerorientierte IR-Tradition. Es zeigt, welche anderen (als nur die labororientierten) IR-Studien durchgeführt werden können, wobei sich die Betrachtung von frühen Modellen (z.B. Taylor) über Belkins ASK-Konzept bis zu Ingwersens Modell der Polyrepräsentation, und von Bates Berrypicking-Ansatz bis zu Vakkaris "taskbased" IR-Modell erstreckt. Auch Web-IR, OKAPI und Diskussionen zum Relevanzbegriff werden hier thematisiert. - Im folgenden Kapitel schlagen die Autoren ein integriertes IS&R Forschungsmodell vor, bei dem die vielfältigen Beziehungen zwischen Informationssuchenden, Systementwicklern, Oberflächen und anderen beteiligten Aspekten berücksichtigt werden. Ihr Ansatz vereint die traditionelle Laborforschung mit verschiedenen benutzerorientierten Traditionen aus IS&R, insbesondere mit den empirischen Ansätzen zu IS und zum interaktiven IR, in einem holistischen kognitiven Modell. - Kapitel sieben untersucht die Implikationen dieses Modells für IS&R, wobei besonders ins Auge fällt, wie komplex die Anfragen von Informationssuchenden im Vergleich mit der relativen Einfachheit der Algorithmen zum Auffinden relevanter Dokumente sind. Die Abbildung der vielfältig variierenden kognitiven Zustände der Anfragesteller im Rahmen der der Systementwicklung ist sicherlich keine triviale Aufgabe. Wie dabei das Problem der Einbeziehung des zentralen Aspektes der Bedeutung gelöst werden kann, sei dahingestellt. - Im achten Kapitel wird der Versuch unternommen, die zuvor diskutierten Punkte in ein IS&R-Forschungsprogramm (Prozesse - Verhalten - Systemfunktionalität - Performanz) umzusetzen, wobei auch einige kritische Anmerkungen zur bisherigen Forschungspraxis getroffen werden. - Das abschliessende neunte Kapitel fasst das Buch kurz zusammen und kann somit auch als Einstieg in dieThematik gelesen werden. Darauffolgen noch ein sehr nützliches Glossar zu allen wichtigen Begriffen, die in dem Buch Verwendung finden, eine Bibliographie und ein Sachregister. Ingwersen und Järvelin haben hier ein sehr anspruchsvolles und dennoch lesbares Buch vorgelegt. Die gebotenen Übersichtskapitel und Diskussionen sind zwar keine Einführung in die Informationswissenschaft, decken aber einen grossen Teil der heute in dieser Disziplin aktuellen und durch laufende Forschungsaktivitäten und Publikationen berührten Teilbereiche ab. Man könnte es auch - vielleicht ein wenig überspitzt - so formulieren: Was hier thematisiert wird, ist eigentlich die moderne Informationswissenschaft. Der Versuch, die beiden Forschungstraditionen zu vereinen, wird diesem Werk sicherlich einen Platz in der Geschichte der Disziplin sichern. Nicht ganz glücklich erscheint der Titel des Buches. "The Turn" soll eine Wende bedeuten, nämlich jene hin zu einer integrierten Sicht von IS und IR. Das geht vermutlich aus dem Untertitel besser hervor, doch dieser erschien den Autoren wohl zu trocken. Schade, denn "The Turn" gibt es z.B. in unserem Verbundkatalog bereits, allerdings mit dem Zusatz "from the Cold War to a new era; the United States and the Soviet Union 1983-1990". Der Verlag, der abgesehen davon ein gediegenes (wenn auch nicht gerade wohlfeiles) Produkt vorgelegt hat, hätte derlei unscharfe Duplizierend besser verhindert. Ungeachtet dessen empfehle ich dieses wichtige Buch ohne Vorbehalt zur Anschaffung; es sollte in keiner grösseren Bibliothek fehlen."

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Abstract

A model of browsing-based conceptual information retrieval is proposed employing two different types of dictionaries, a global dictionary and a local dictionary. A global dictionary with the authorized terms is utilized to capture the commonly acknowledgeable conceptual relation between a query and a document by replacing their keywords with the dictionary terms. The documents are ranked by the conceptual closeness to a query, and are arranged in the form of a user's personal digital library, or pDL. In a pDL a user can browse the arranged documents based an a suggestion about which documents are worth examining. This suggestion is made by the information in a local dictionary that is organized so as to reflect a user's interest and the association of keywords with the documents. Experiments for testing the retrieval performance of utilizing the two types of dictionaries were also performed using Standard test collections.

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Abstract

A means of automatically deriving a hierarchical organization of concepts from a set of documents without use of training data or standard clustering techniques is presented. Using a process that extracts salient words and phrases from the documents, these terms are organized hierarchically using a type of co-occurrence known as subsumption. The resulting structure is displayed as a series of hierarchical menus. When generated from a set of retrieved documents, a user browsing the menus gains an overview of their content in a manner distinct from existing techniques. The methods used to build the structure are simple and appear to be effective. The formation and presentation of the hierarchy is described along with a study of some of its properties, including a preliminary experiment, which indicates that users may find the hierarchy a more efficient means of locating relevant documents than the classic method of scanning a ranked document list

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Abstract

The authors present a model of information searching in thesaurus-enhanced search systems, intended as a reference model for system developers. The model focuses on user-system interaction and charts the specific stages of searching an indexed collection with a thesaurus. It was developed based on literature, findings from empirical studies, and analysis of existing systems. The model describes in detail the entities, processes, and decisions when interacting with a search system augmented with a thesaurus. A basic search scenario illustrates this process through the model. Graphical and textual depictions of the model are complemented by a concise matrix representation for evaluation purposes. Potential problems at different stages of the search process are discussed, together with possibilities for system developers. The aim is to set out a framework of processes, decisions, and risks involved in thesaurus-based search, within which system developers can consider potential avenues for support.

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Abstract

This article shows how a fuzzy ontology-based approach can improve semantic documents retrieval. After formally defining a fuzzy ontology and a fuzzy knowledge base, a special type of new fuzzy relationship called (semantic) correlation, which links the concepts or entities in a fuzzy ontology, is discussed. These correlations, first assigned by experts, are updated after querying or when a document has been inserted into a database. Moreover, in order to define a dynamic knowledge of a domain adapting itself to the context, it is shown how to handle a tradeoff between the correct definition of an object, taken in the ontology structure, and the actual meaning assigned by individuals. The notion of a fuzzy concept network is extended, incorporating database objects so that entities and documents can similarly be represented in the network. Information retrieval (IR) algorithm, using an object-fuzzy concept network (O-FCN), is introduced and described. This algorithm allows us to derive a unique path among the entities involved in the query to obtain maxima semantic associations in the knowledge domain. Finally, the study has been validated by querying a database using fuzzy recall, fuzzy precision, and coefficient variant measures in the crisp and fuzzy cases.

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Abstract

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.

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