Search (12 results, page 1 of 1)

  • × author_ss:"Beheshti, J."
  1. Cole, C.; Beheshti, J.; Leide, J. E.; Large, A.: Interactive information retrieval : bringing the user to a selection state (2005) 0.01
    0.005069189 = product of:
      0.03548432 = sum of:
        0.03548432 = product of:
          0.0887108 = sum of:
            0.029295133 = weight(_text_:retrieval in 36) [ClassicSimilarity], result of:
              0.029295133 = score(doc=36,freq=8.0), product of:
                0.109568894 = queryWeight, product of:
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.03622214 = queryNorm
                0.26736724 = fieldWeight in 36, product of:
                  2.828427 = tf(freq=8.0), with freq of:
                    8.0 = termFreq=8.0
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.03125 = fieldNorm(doc=36)
            0.059415665 = weight(_text_:system in 36) [ClassicSimilarity], result of:
              0.059415665 = score(doc=36,freq=28.0), product of:
                0.11408355 = queryWeight, product of:
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.03622214 = queryNorm
                0.52080834 = fieldWeight in 36, product of:
                  5.2915025 = tf(freq=28.0), with freq of:
                    28.0 = termFreq=28.0
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.03125 = fieldNorm(doc=36)
          0.4 = coord(2/5)
      0.14285715 = coord(1/7)
    
    Abstract
    There have been various approaches to conceptualizing interactive information retrieval (IR), which can be generally divided into system and user approaches (Hearst, 1999; cf. also Spink, 1997). Both system and user approaches define user-system interaction in terms of the system and the user reacting to the actions or behaviors of the other: the system reacts to the user's input; the user to the output of the system (Spink, 1997). In system approach models of the interaction, e.g., Moran (1981), "[T]he user initiates an action or operation and the system responds in some way which in turn leads the user to initiate another action and so on" (Beaulieu, 2000, p. 433). In its purest form, the system approach models the user as a reactive part of the interaction, with the system taking the lead (Bates, 1990). User approaches, on the other hand, in their purest form wish to insert a model of the user in all its socio-cognitive dimensions, to the extent that system designers consider such approaches impractical (Vakkari and Jarvelin, 2005, Chap. 7, this volume). The cognitive approach to IR interaction attempts to overcome this divide (Ruthven, 2005, Chap. 4, this volume; Vakkari and Jarvelin, 2005 Chap. 7, this volume) by representing the cognitive elements of both system designers and the user in the interaction model (Larsen and Ingwersen, 2005 Chap. 3, this volume). There are cognitive approach researchers meeting in a central ground from both the system and user side. On the system side, are computer scientists employing cognitive research to design more effective IR systems from the point of view of the user's task (Nathan, 1990; Fischer, Henninger, and Redmiles, 1991; O'Day and Jeffries, 1993; Russell et al., 1993; Kitajima and Polson, 1996; Terwilliger and Polson, 1997). On the user side are cognitive approach researchers applying methods, concepts and models from psychology to design systems that are more in tune with how users acquire information (e.g., Belkin, 1980; Ford (2005, Chap. 5, this volume); Ingwersen (Larsen and Ingwersen, 2005, Chap. 3, this volume); Saracevic, 1996; Vakkari (Vakkari and Jarvelin, 2005, Chap. 7, this volume)).
    Series
    The information retrieval series, vol. 19
    Source
    New directions in cognitive information retrieval. Eds.: A. Spink, C. Cole
  2. Cole, C.; Leide, J.E.; Large, A,; Beheshti, J.; Brooks, M.: Putting it together online : information need identification for the domain novice user (2005) 0.00
    0.003444207 = product of:
      0.024109447 = sum of:
        0.024109447 = product of:
          0.060273618 = sum of:
            0.025893483 = weight(_text_:retrieval in 3469) [ClassicSimilarity], result of:
              0.025893483 = score(doc=3469,freq=4.0), product of:
                0.109568894 = queryWeight, product of:
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.03622214 = queryNorm
                0.23632148 = fieldWeight in 3469, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3469)
            0.034380134 = weight(_text_:system in 3469) [ClassicSimilarity], result of:
              0.034380134 = score(doc=3469,freq=6.0), product of:
                0.11408355 = queryWeight, product of:
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.03622214 = queryNorm
                0.30135927 = fieldWeight in 3469, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3469)
          0.4 = coord(2/5)
      0.14285715 = coord(1/7)
    
    Abstract
    Domain novice users in the beginning stages of researching a topic find themselves searching for information via information retrieval (IR) systems before they have identified their information need. Pre-Internet access technologies adapted by current IR systems poorly serve these domain novice users, whose behavior might be characterized as rudderless and without a compass. In this article we describe a conceptual design for an information retrieval system that incorporates standard information need identification classification and subject cataloging schemes, called the INIIReye System, and a study that tests the efficacy of the innovative part of the INIIReye System, called the Associative Index. The Associative Index helps the user put together his or her associative thoughts-Vannevar Bush's idea of associative indexing for his Memex machine that he never actually described. For the first time, data from the study reported here quantitatively supports the theoretical notion that the information seeker's information need is identified through transformation of his/her knowledge structure (i.e., the seeker's cognitive map or perspective an the task far which information is being sought).
  3. Leide, J.E.; Cole, C.; Beheshti, J.; Large, A.; Lin, Y.: Task-based information retrieval : structuring undergraduate history essays for better course evaluation using essay-type visualizations (2007) 0.00
    0.002613878 = product of:
      0.018297145 = sum of:
        0.018297145 = product of:
          0.045742862 = sum of:
            0.025893483 = weight(_text_:retrieval in 460) [ClassicSimilarity], result of:
              0.025893483 = score(doc=460,freq=4.0), product of:
                0.109568894 = queryWeight, product of:
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.03622214 = queryNorm
                0.23632148 = fieldWeight in 460, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=460)
            0.01984938 = weight(_text_:system in 460) [ClassicSimilarity], result of:
              0.01984938 = score(doc=460,freq=2.0), product of:
                0.11408355 = queryWeight, product of:
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.03622214 = queryNorm
                0.17398985 = fieldWeight in 460, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=460)
          0.4 = coord(2/5)
      0.14285715 = coord(1/7)
    
    Abstract
    When domain novices are in C.C. Kuhlthau's (1993) Stage 3, the exploration stage of researching an assignment, they often do not know their information need; this causes them to go back to Stage 2, the topic-selection stage, when they are selecting keywords to formulate their query to an Information Retrieval (IR) system. Our hypothesis is that instead of going backward, they should be going forward toward a goal state-the performance of the task for which they are seeking the information. If they can somehow construct their goal state into a query, this forward-looking query better operationalizes their information need than does a topic-based query. For domain novice undergraduates seeking information for a course essay, we define their task as selecting a high-impact essay structure which will put the students' learning on display for the course instructor who will evaluate the essay. We report a study of first-year history undergraduate students which tested the use and effectiveness of "essay type" as a task-focused query-formulation device. We randomly assigned 78 history undergraduates to an intervention group and a control group. The dependent variable was essay quality, based on (a) an evaluation of the student's essay by a research team member, and (b) the marks given to the student's essay by the course instructor. We found that conscious or formal consideration of essay type is inconclusive as a basis of a task-focused query-formulation device for IR.
  4. Beheshti, J.; Bowler, L.; Large, A.; Nesset, V.: Towards an alternative information retrieval system for children (2005) 0.00
    0.0025814078 = product of:
      0.018069854 = sum of:
        0.018069854 = product of:
          0.045174636 = sum of:
            0.029295133 = weight(_text_:retrieval in 644) [ClassicSimilarity], result of:
              0.029295133 = score(doc=644,freq=8.0), product of:
                0.109568894 = queryWeight, product of:
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.03622214 = queryNorm
                0.26736724 = fieldWeight in 644, product of:
                  2.828427 = tf(freq=8.0), with freq of:
                    8.0 = termFreq=8.0
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.03125 = fieldNorm(doc=644)
            0.015879504 = weight(_text_:system in 644) [ClassicSimilarity], result of:
              0.015879504 = score(doc=644,freq=2.0), product of:
                0.11408355 = queryWeight, product of:
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.03622214 = queryNorm
                0.13919188 = fieldWeight in 644, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.03125 = fieldNorm(doc=644)
          0.4 = coord(2/5)
      0.14285715 = coord(1/7)
    
    Abstract
    A recent survey of more than 1700 households indicates that the main reason many parents purchase computers and connect their children to the Internet at home is for education (Safe and Smart). In addition the survey shows that children also use the Internet for educational activities that go beyond required school work. In fact, the fastest growing group of Internet users are children between the ages of eight and twelve (Vise, 2003), who are increasingly using the Web to access educational as well as entertainment materials. Children, however, rely on conventional information retrieval (IR) systems and search engines intended for general adult use, such as MSN or Google, and to a much lesser extent, Web portals such as Yahooligans! and LycosZone specifically intended for young users (Large et al., 2004; Large, Beheshti, and Rahman, 2002a). But research has shown that children's information needs (Walter, 1994), research approaches (Kuhlthau, 1991), and cognitive abilities and higher order thinking skills (Neuman, 1995; Siegler, 1998; Vandergrift, 1989) differ from those of adults. The results of earlier studies on children's use of online catalogues designed for adults indicate that young users are often faced with difficulties locating specific information related to their information needs (Hirsh, 1997). A growing body of research points to the problems children typically encounter when seeking information on the Web. Kafai and Bates (1997) conducted one of the first studies with young children on their use of Web sites, and concluded that they were able to navigate through the links and scroll. Only the older children, however, could use search engines effectively. Hirsh (1999) investigated the searching behavior of ten fifth graders and concluded that they encountered difficulties in formulating effective search queries and did not use advanced features. Schacter, Chung, and Dorr (1998) conducted a study on Internet searching by fifth and sixth graders and concluded that they did not plan their searches, used ill-defined queries, and preferred browsing. Large, Beheshti, and Moukdad (1999), investigating the information seeking behavior of 53 sixth graders, similarly found that children preferred browsing to searching. Bowler, Large, and Rejskind (2001), focusing on a few case studies of grade six students concluded that search engines designed for adults are unsuitable for children. Wallace et al. (2000), studying sixth graders, discovered that experience in using search engines does not improve children's search strategies and in general information seeking is an unfamiliar activity for children.
    Series
    The information retrieval series, vol. 19
    Source
    New directions in cognitive information retrieval. Eds.: A. Spink, C. Cole
  5. Large, A.; Beheshti, J.; Rahman, T.: Design criteria for children's Web portals : the users speak out (2002) 0.00
    0.0021032572 = product of:
      0.0147228 = sum of:
        0.0147228 = product of:
          0.0294456 = sum of:
            0.0294456 = weight(_text_:22 in 197) [ClassicSimilarity], result of:
              0.0294456 = score(doc=197,freq=2.0), product of:
                0.12684377 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.03622214 = queryNorm
                0.23214069 = fieldWeight in 197, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.046875 = fieldNorm(doc=197)
          0.5 = coord(1/2)
      0.14285715 = coord(1/7)
    
    Date
    2. 6.2005 10:34:22
  6. Beheshti, J.: Retrieval interfaces for CD-ROM bibliographic databases (1991) 0.00
    0.0016740077 = product of:
      0.011718053 = sum of:
        0.011718053 = product of:
          0.058590267 = sum of:
            0.058590267 = weight(_text_:retrieval in 3994) [ClassicSimilarity], result of:
              0.058590267 = score(doc=3994,freq=2.0), product of:
                0.109568894 = queryWeight, product of:
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.03622214 = queryNorm
                0.5347345 = fieldWeight in 3994, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.125 = fieldNorm(doc=3994)
          0.2 = coord(1/5)
      0.14285715 = coord(1/7)
    
  7. Large, A.; Beheshti, J.; Breuleux, A.: ¬A comparison of information retrieval from print and CD-ROM versions of an encyclopedia by elementary school students (1994) 0.00
    0.0014647568 = product of:
      0.010253297 = sum of:
        0.010253297 = product of:
          0.051266484 = sum of:
            0.051266484 = weight(_text_:retrieval in 1015) [ClassicSimilarity], result of:
              0.051266484 = score(doc=1015,freq=8.0), product of:
                0.109568894 = queryWeight, product of:
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.03622214 = queryNorm
                0.46789268 = fieldWeight in 1015, product of:
                  2.828427 = tf(freq=8.0), with freq of:
                    8.0 = termFreq=8.0
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=1015)
          0.2 = coord(1/5)
      0.14285715 = coord(1/7)
    
    Abstract
    Describes an experiment using 48 sixth-grade students to compare retrieval techniques using the print and CD-ROM versions of Compton's Encyclopedia. Four queries of defferent complexity (measured by the numer of terms present) were searched by the students after a short training session. The searches were timed and the retrieval steps and search terms were noted. The searches were no faster on the CD-ROM than the print version, but in both cases time was related directly to the number of terms involved. The students coped well with the CD-ROM interface and its several retrieval paths
  8. Beheshti, J.; Large, V.; Bialek, M.: PACE: a browsable graphical interface (1996) 0.00
    0.0010357393 = product of:
      0.007250175 = sum of:
        0.007250175 = product of:
          0.036250874 = sum of:
            0.036250874 = weight(_text_:retrieval in 7685) [ClassicSimilarity], result of:
              0.036250874 = score(doc=7685,freq=4.0), product of:
                0.109568894 = queryWeight, product of:
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.03622214 = queryNorm
                0.33085006 = fieldWeight in 7685, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=7685)
          0.2 = coord(1/5)
      0.14285715 = coord(1/7)
    
    Abstract
    PACE (Public Access Catalogue Extension) is an alternative user interface designed to enhace OPACs. PACE simulates images of books and library shelves to help users browse through the catalogue. Reports results of a study in which PACE was tested in a college library (Vanier College), in a real operational environment, against a second generation test based OPAC: Best-Seller. Results show that a simple browsable retrieval interface performed as well as a second generation OPAC in terms of retrieval speed and search success. The overwhelming majority of students, however, preferred the browsing capability of PACE through the familiar metaphor of books and library shelves to a text based OPAC
  9. Large, A.; Beheshti, J.; Breuleux, A.: Multimedia and comprehension : a cognitive study (1994) 0.00
    8.877766E-4 = product of:
      0.006214436 = sum of:
        0.006214436 = product of:
          0.03107218 = sum of:
            0.03107218 = weight(_text_:retrieval in 7754) [ClassicSimilarity], result of:
              0.03107218 = score(doc=7754,freq=4.0), product of:
                0.109568894 = queryWeight, product of:
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.03622214 = queryNorm
                0.2835858 = fieldWeight in 7754, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.046875 = fieldNorm(doc=7754)
          0.2 = coord(1/5)
      0.14285715 = coord(1/7)
    
    Abstract
    Tests were carried out on 120 grade 6 students to compare Compton's Multimedia Encyclopedia on CD-ROM and its printe equivalent in terms of students' ability to recall information and to draw inferences from it. Between-subject varaibles were 3 presentation conditions (printed text with illustrations, text-on-screen, and multimedia-text, still images, and animation) and a retrieval condition (topic retrieved before viewing / topic presented without retrieval). Within-subject variables were text complexity (complex or simple), text type (descriptive or procedural), and measure (propositions recalled versus propositions inferred). Presentation conditions produced no significant main effect although text-on-screen resulted in somewhat higher recall and multimedia resulted in somewhat higher inference scores. Multimedia had the greatest effect in the case of simple topics, and especially the simple procedural topic
  10. Leide, J.E.; Large, A.; Beheshti, J.; Brooks, M.; Cole, C.: Visualization schemes for domain novices exploring a topic space : the navigation classification scheme (2003) 0.00
    8.0203614E-4 = product of:
      0.0056142528 = sum of:
        0.0056142528 = product of:
          0.028071264 = sum of:
            0.028071264 = weight(_text_:system in 1078) [ClassicSimilarity], result of:
              0.028071264 = score(doc=1078,freq=4.0), product of:
                0.11408355 = queryWeight, product of:
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.03622214 = queryNorm
                0.24605882 = fieldWeight in 1078, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1078)
          0.2 = coord(1/5)
      0.14285715 = coord(1/7)
    
    Abstract
    In this article and two other articles which conceptualize a future stage of the research program (Leide, Cole, Large, & Beheshti, submitted for publication; Cole, Leide, Large, Beheshti, & Brooks, in preparation), we map-out a domain novice user's encounter with an IR system from beginning to end so that appropriate classification-based visualization schemes can be inserted into the encounter process. This article describes the visualization of a navigation classification scheme only. The navigation classification scheme uses the metaphor of a ship and ship's navigator traveling through charted (but unknown to the user) waters, guided by a series of lighthouses. The lighthouses contain mediation interfaces linking the user to the information store through agents created for each. The user's agent is the cognitive model the user has of the information space, which the system encourages to evolve via interaction with the system's agent. The system's agent is an evolving classification scheme created by professional indexers to represent the structure of the information store. We propose a more systematic, multidimensional approach to creating evolving classification/indexing schemes, based on where the user is and what she is trying to do at that moment during the search session.
  11. Yi, K.; Beheshti, J.; Cole, C.; Leide, J.E.; Large, A.: User search behavior of domain-specific information retrieval systems : an analysis of the query logs from PsycINFO and ABC-Clio's Historical Abstracts/America: History and Life (2006) 0.00
    5.2312744E-4 = product of:
      0.003661892 = sum of:
        0.003661892 = product of:
          0.01830946 = sum of:
            0.01830946 = weight(_text_:retrieval in 197) [ClassicSimilarity], result of:
              0.01830946 = score(doc=197,freq=2.0), product of:
                0.109568894 = queryWeight, product of:
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.03622214 = queryNorm
                0.16710453 = fieldWeight in 197, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=197)
          0.2 = coord(1/5)
      0.14285715 = coord(1/7)
    
  12. Cole, C.; Lin, Y.; Leide, J.; Large, A.; Beheshti, J.: ¬A classification of mental models of undergraduates seeking information for a course essay in history and psychology : preliminary investigations into aligning their mental models with online thesauri (2007) 0.00
    4.5370017E-4 = product of:
      0.003175901 = sum of:
        0.003175901 = product of:
          0.015879504 = sum of:
            0.015879504 = weight(_text_:system in 625) [ClassicSimilarity], result of:
              0.015879504 = score(doc=625,freq=2.0), product of:
                0.11408355 = queryWeight, product of:
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.03622214 = queryNorm
                0.13919188 = fieldWeight in 625, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.03125 = fieldNorm(doc=625)
          0.2 = coord(1/5)
      0.14285715 = coord(1/7)
    
    Abstract
    The article reports a field study which examined the mental models of 80 undergraduates seeking information for either a history or psychology course essay when they were in an early, exploration stage of researching their essay. This group is presently at a disadvantage when using thesaurus-type schemes in indexes and online search engines because there is a disconnect between how domain novice users of IR systems represent a topic space and how this space is represented in the standard IR system thesaurus. The study attempted to (a) ascertain the coding language used by the 80 undergraduates in the study to mentally represent their topic and then (b) align the mental models with the hierarchical structure found in many thesauri. The intervention focused the undergraduates' thinking about their topic from a topic statement to a thesis statement. The undergraduates were asked to produce three mental model diagrams for their real-life course essay at the beginning, middle, and end of the interview, for a total of 240 mental model diagrams, from which we created a 12-category mental model classification scheme. Findings indicate that at the end of the intervention, (a) the percentage of vertical mental models increased from 24 to 35% of all mental models; but that (b) 3rd-year students had fewer vertical mental models than did 1st-year undergraduates in the study, which is counterintuitive. The results indicate that there is justification for pursuing our research based on the hypothesis that rotating a domain novice's mental model into a vertical position would make it easier for him or her to cognitively connect with the thesaurus's hierarchical representation of the topic area.