Search (12 results, page 1 of 1)

0.026846847 = product of:
  0.20135134 = sum of:
    0.072100736 = weight(_text_:web in 1070) [ClassicSimilarity], result of:
      0.072100736 = score(doc=1070,freq=30.0), product of:
        0.10326045 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.031640913 = queryNorm
        0.69824153 = fieldWeight in 1070, product of:
          5.477226 = tf(freq=30.0), with freq of:
            30.0 = termFreq=30.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1070)
    0.1292506 = weight(_text_:site in 1070) [ClassicSimilarity], result of:
      0.1292506 = score(doc=1070,freq=12.0), product of:
        0.1738463 = queryWeight, product of:
          5.494352 = idf(docFreq=493, maxDocs=44218)
          0.031640913 = queryNorm
        0.7434763 = fieldWeight in 1070, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          5.494352 = idf(docFreq=493, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1070)
  0.13333334 = coord(2/15)

Abstract

Automatic categorization is a viable method to deal with the scaling problem on the World Wide Web. For Web site classification, this paper proposes the use of Web pages linked with the home page in a different manner from the sole use of home pages in previous research. To implement our proposed method, we derive a scheme for Web site classification based on the k-nearest neighbor (k-NN) approach. It consists of three phases: Web page selection (connectivity analysis), Web page classification, and Web site classification. Given a Web site, the Web page selection chooses several representative Web pages using connectivity analysis. The k-NN classifier next classifies each of the selected Web pages. Finally, the classified Web pages are extended to a classification of the entire Web site. To improve performance, we supplement the k-NN approach with a feature selection method and a term weighting scheme using markup tags, and also reform its document-document similarity measure. In our experiments on a Korean commercial Web directory, the proposed system, using both a home page and its linked pages, improved the performance of micro-averaging breakeven point by 30.02%, compared with an ordinary classification which uses a home page only.

0.009630497 = product of:
  0.07222872 = sum of:
    0.061511453 = weight(_text_:evaluation in 2845) [ClassicSimilarity], result of:
      0.061511453 = score(doc=2845,freq=8.0), product of:
        0.13272417 = queryWeight, product of:
          4.1947007 = idf(docFreq=1811, maxDocs=44218)
          0.031640913 = queryNorm
        0.4634533 = fieldWeight in 2845, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          4.1947007 = idf(docFreq=1811, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2845)
    0.010717267 = product of:
      0.021434534 = sum of:
        0.021434534 = weight(_text_:22 in 2845) [ClassicSimilarity], result of:
          0.021434534 = score(doc=2845,freq=2.0), product of:
            0.110801086 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.031640913 = queryNorm
            0.19345059 = fieldWeight in 2845, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2845)
      0.5 = coord(1/2)
  0.13333334 = coord(2/15)

Abstract

The music information retrieval (MIR) community has long understood the role of evaluation as a critical component for successful information retrieval systems. Over the past several years, it has also become evident that user-centered evaluation based on realistic tasks is essential for creating systems that are commercially marketable. Although user-oriented research has been increasing, the MIR field is still lacking in holistic, user-centered approaches to evaluating music services beyond measuring the performance of search or classification algorithms. In light of this need, we conducted a user study exploring how users evaluate their overall experience with existing popular commercial music services, asking about their interactions with the system as well as situational and personal characteristics. In this paper, we present a qualitative heuristic evaluation of commercial music services based on Jakob Nielsen's 10 usability heuristics for user interface design, and also discuss 8 additional criteria that may be used for the holistic evaluation of user experience in MIR systems. Finally, we recommend areas of future user research raised by trends and patterns that surfaced from this user study.

Date

17. 3.2016 19:22:15

0.0069592274 = product of:
  0.10438841 = sum of:
    0.10438841 = weight(_text_:evaluation in 3321) [ClassicSimilarity], result of:
      0.10438841 = score(doc=3321,freq=16.0), product of:
        0.13272417 = queryWeight, product of:
          4.1947007 = idf(docFreq=1811, maxDocs=44218)
          0.031640913 = queryNorm
        0.7865064 = fieldWeight in 3321, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          4.1947007 = idf(docFreq=1811, maxDocs=44218)
          0.046875 = fieldNorm(doc=3321)
  0.06666667 = coord(1/15)

Abstract

Music Information Retrieval (MIR) evaluation has traditionally focused on system-centered approaches where components of MIR systems are evaluated against predefined data sets and golden answers (i.e., ground truth). There are two major limitations of such system-centered evaluation approaches: (a) The evaluation focuses on subtasks in music information retrieval, but not on entire systems and (b) users and their interactions with MIR systems are largely excluded. This article describes the first implementation of a holistic user-experience evaluation in MIR, the MIREX Grand Challenge, where complete MIR systems are evaluated, with user experience being the single overarching goal. It is the first time that complete MIR systems have been evaluated with end users in a realistic scenario. We present the design of the evaluation task, the evaluation criteria and a novel evaluation interface, and the data-collection platform. This is followed by an analysis of the results, reflection on the experience and lessons learned, and plans for future directions.

0.0068726577 = product of:
  0.05154493 = sum of:
    0.008049765 = product of:
      0.01609953 = sum of:
        0.01609953 = weight(_text_:online in 3454) [ClassicSimilarity], result of:
          0.01609953 = score(doc=3454,freq=2.0), product of:
            0.096027054 = queryWeight, product of:
              3.0349014 = idf(docFreq=5778, maxDocs=44218)
              0.031640913 = queryNorm
            0.16765618 = fieldWeight in 3454, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0349014 = idf(docFreq=5778, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3454)
      0.5 = coord(1/2)
    0.043495167 = weight(_text_:evaluation in 3454) [ClassicSimilarity], result of:
      0.043495167 = score(doc=3454,freq=4.0), product of:
        0.13272417 = queryWeight, product of:
          4.1947007 = idf(docFreq=1811, maxDocs=44218)
          0.031640913 = queryNorm
        0.327711 = fieldWeight in 3454, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.1947007 = idf(docFreq=1811, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3454)
  0.13333334 = coord(2/15)

Abstract

Our limited understanding of real-life queries is an obstacle in developing music information retrieval (MIR) systems that meet the needs of real users. This study aimed, by an empirical investigation of real-life queries, to contribute to developing a theorized understanding of how users seek music information. This is crucial for informing the design of future MIR systems, especially the selection of potential access points, as well as establishing a set of test queries that reflect real-life music information-seeking behavior. Natural language music queries were collected from an online reference Website and coded using content analysis. A taxonomy of user needs expressed and information features used in queries were established by an iterative coding process. This study found that most of the queries analyzed were known-item searches, and most contained a wide variety of kinds of information, although a few features were used much more heavily than the others. In addition to advancing our understanding of real-life user queries by establishing an improved taxonomy of needs and features, three recommendations were made for improving the evaluation of MIR systems: (i) incorporating user context in test queries, (ii) employing terms familiar to users in evaluation tasks, and (iii) combining multiple task results.

0.002899678 = product of:
  0.043495167 = sum of:
    0.043495167 = weight(_text_:evaluation in 2343) [ClassicSimilarity], result of:
      0.043495167 = score(doc=2343,freq=4.0), product of:
        0.13272417 = queryWeight, product of:
          4.1947007 = idf(docFreq=1811, maxDocs=44218)
          0.031640913 = queryNorm
        0.327711 = fieldWeight in 2343, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.1947007 = idf(docFreq=1811, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2343)
  0.06666667 = coord(1/15)

Abstract

Despite increasing interest in and acknowledgment of the significance of video games, current descriptive practices are not sufficiently robust to support searching, browsing, and other access behaviors from diverse user groups. To address this issue, the Game Metadata Research Group at the University of Washington Information School, in collaboration with the Seattle Interactive Media Museum, worked to create a standardized metadata schema. This metadata schema was empirically evaluated using multiple approaches-collaborative review, schema testing, semi-structured user interview, and a large-scale survey. Reviewing and testing the schema revealed issues and challenges in sourcing the metadata for particular elements, determining the level of granularity for data description, and describing digitally distributed games. The findings from user studies suggest that users value various subject and visual metadata, information about how games are related to each other, and data regarding game expansions/alterations such as additional content and networked features. The metadata schema was extensively revised based on the evaluation results, and we present the new element definitions from the revised schema in this article. This work will serve as a platform and catalyst for advances in the design and use of video game metadata.

0.0028705348 = product of:
  0.04305802 = sum of:
    0.04305802 = weight(_text_:evaluation in 6729) [ClassicSimilarity], result of:
      0.04305802 = score(doc=6729,freq=2.0), product of:
        0.13272417 = queryWeight, product of:
          4.1947007 = idf(docFreq=1811, maxDocs=44218)
          0.031640913 = queryNorm
        0.32441732 = fieldWeight in 6729, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.1947007 = idf(docFreq=1811, maxDocs=44218)
          0.0546875 = fieldNorm(doc=6729)
  0.06666667 = coord(1/15)

Abstract

There have been several document ranking methods to calculate the conceptual distance or closeness between a Boolean query and a document. Though they provide good retrieval effectiveness in many cases, they do not support effective weighting schemes for queries and documents and also have several problems resulting from inappropriate evaluation of Boolean operators. We propose a new method called Knowledge-Based Extended Boolean Model (KB-EBM) in which Salton's extended Boolean model is incorporated. KB-EBM evaluates weighted queries and documents effectively, and avoids the problems of the previous methods. KB-EBM provides high quality document rankings by using term dependence information from is-a hierarchies. The performance experiments show that the proposed method closely simulates human behaviour

0.0012410887 = product of:
  0.01861633 = sum of:
    0.01861633 = weight(_text_:web in 3596) [ClassicSimilarity], result of:
      0.01861633 = score(doc=3596,freq=2.0), product of:
        0.10326045 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.031640913 = queryNorm
        0.18028519 = fieldWeight in 3596, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3596)
  0.06666667 = coord(1/15)

Abstract

Recent, rapid changes in technology have resulted in a proliferation of choices for music storage and access. Portable, web-enabled music devices are widespread, and listeners now enjoy a plethora of options regarding formats, devices, and access methods. Yet in this mobile music environment, listeners' access and management strategies for music collections are poorly understood, because behaviors surrounding the organization and retrieval of music collections have received little formal study. Our current research seeks to enrich our knowledge of people's music listening and collecting behavior through a series of systematic user studies. In this paper we present our findings from interviews involving 20 adult and 20 teen users of commercial cloud music services. Our results contribute to theoretical understandings of users' music information behavior in a time of upheaval in music usage patterns, and more generally, the purposes and meanings users ascribe to personal media collections in cloud-based systems. The findings suggest improvements to the future design of cloud-based music services, as well as to any information systems and services designed for personal media collections, benefiting both commercial entities and listeners.

0.0012410887 = product of:
  0.01861633 = sum of:
    0.01861633 = weight(_text_:web in 3958) [ClassicSimilarity], result of:
      0.01861633 = score(doc=3958,freq=2.0), product of:
        0.10326045 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.031640913 = queryNorm
        0.18028519 = fieldWeight in 3958, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3958)
  0.06666667 = coord(1/15)

Abstract

Currently, there is no structured data standard for representing elements commonly found in transmedia fictional worlds. Although there are websites dedicated to individual universes, the information found on these sites separate out the various formats, concentrate on only the bibliographic aspects of the material, and are only searchable with full text. We have created an ontological model that will allow various user groups interested in transmedia to search for and retrieve the information contained in these worlds based upon their structure. We conducted a domain analysis and user studies based on the contents of Harry Potter, Lord of the Rings, the Marvel Universe, and Star Wars in order to build a new model using Ontology Web Language (OWL) and an artificial intelligence-reasoning engine. This model can infer connections between transmedia properties such as characters, elements of power, items, places, events, and so on. This model will facilitate better search and retrieval of the information contained within these vast story universes for all users interested in them. The result of this project is an OWL ontology reflecting real user needs based upon user research, which is intuitive for users and can be used by artificial intelligence systems.

7.1448454E-4 = product of:
  0.010717267 = sum of:
    0.010717267 = product of:
      0.021434534 = sum of:
        0.021434534 = weight(_text_:22 in 4218) [ClassicSimilarity], result of:
          0.021434534 = score(doc=4218,freq=2.0), product of:
            0.110801086 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.031640913 = queryNorm
            0.19345059 = fieldWeight in 4218, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4218)
      0.5 = coord(1/2)
  0.06666667 = coord(1/15)

Abstract

The discovery and retrieval of video games in library and information systems is, by and large, dependent on a limited set of descriptive metadata. Noticeably missing from this metadata are classifications of visual style-despite the overwhelmingly visual nature of most video games and the interest in visual style among video game users. One explanation for this paucity is the difficulty in eliciting consistent judgements about visual style, likely due to subjective interpretations of terminology and a lack of demonstrable testing for coinciding judgements. This study presents a taxonomy of video game visual styles constructed from the findings of a 22-participant cataloging user study of visual styles. A detailed description of the study, and its value and shortcomings, are presented along with reflections about the challenges of cultivating consensus about visual style in video games. The high degree of overall agreement in the user study demonstrates the potential value of a descriptor like visual style and the use of a cataloging study in developing visual style taxonomies. The resulting visual style taxonomy, the methods and analysis described herein may help improve the organization and retrieval of video games and possibly other visual materials like graphic designs, illustrations, and animations.

7.1448454E-4 = product of:
  0.010717267 = sum of:
    0.010717267 = product of:
      0.021434534 = sum of:
        0.021434534 = weight(_text_:22 in 996) [ClassicSimilarity], result of:
          0.021434534 = score(doc=996,freq=2.0), product of:
            0.110801086 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.031640913 = queryNorm
            0.19345059 = fieldWeight in 996, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=996)
      0.5 = coord(1/2)
  0.06666667 = coord(1/15)

Date

22. 6.2023 18:20:47

6.439812E-4 = product of:
  0.009659718 = sum of:
    0.009659718 = product of:
      0.019319436 = sum of:
        0.019319436 = weight(_text_:online in 4535) [ClassicSimilarity], result of:
          0.019319436 = score(doc=4535,freq=2.0), product of:
            0.096027054 = queryWeight, product of:
              3.0349014 = idf(docFreq=5778, maxDocs=44218)
              0.031640913 = queryNorm
            0.20118743 = fieldWeight in 4535, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0349014 = idf(docFreq=5778, maxDocs=44218)
              0.046875 = fieldNorm(doc=4535)
      0.5 = coord(1/2)
  0.06666667 = coord(1/15)

Abstract

Anime, as a growing form of multimedia, needs a better and more thorough organization for its myriad unique terminologies. Existing studies show patrons' desire to search and get recommendations for anime. However, due to inadequate indexing and often confusing or inaccurate usage of terms, searching and acquiring recommendations remain challenging. Our research seeks to close the gap and make discovery and recommendations more viable. In this study, we conducted a facet analysis of anime genre terms that are currently used in thirty-six anime-related English-language databases and websites. Using a card sorting method with an inductive approach to the 1,597 terms collected, we identified and defined nine facets and 153 foci terms that describe different genres of anime. Identified terms can be implemented within different organizational systems including library catalogs, recommendation systems, and online databases to improve genre definitions and search experiences.

6.439812E-4 = product of:
  0.009659718 = sum of:
    0.009659718 = product of:
      0.019319436 = sum of:
        0.019319436 = weight(_text_:online in 5730) [ClassicSimilarity], result of:
          0.019319436 = score(doc=5730,freq=2.0), product of:
            0.096027054 = queryWeight, product of:
              3.0349014 = idf(docFreq=5778, maxDocs=44218)
              0.031640913 = queryNorm
            0.20118743 = fieldWeight in 5730, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0349014 = idf(docFreq=5778, maxDocs=44218)
              0.046875 = fieldNorm(doc=5730)
      0.5 = coord(1/2)
  0.06666667 = coord(1/15)

Abstract

Anime, as a growing form of multimedia, needs a better and more thorough organization for its myriad unique terminologies. Existing studies show patrons' desire to search and get recommendations for anime. However, due to inadequate indexing and often confusing or inaccurate usage of terms, searching and acquiring recommendations remain challenging. Our research seeks to close the gap and make discovery and recommendations more viable. In this study, we conducted a facet analysis of anime genre terms that are currently used in thirty-six anime-related English-language databases and websites. Using a card sorting method with an inductive approach to the 1,597 terms collected, we identified and defined nine facets and 153 foci terms that describe different genres of anime. Identified terms can be implemented within different organizational systems including library catalogs, recommendation systems, and online databases to improve genre definitions and search experiences.