Search (67 results, page 3 of 4)

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Abstract

Understanding the information-seeking behavior of visually impaired users is essential to designing search interfaces that support them during their search tasks. In a previous article, we reported the information-seeking behavior of visually impaired users when performing complex search tasks on the web, and we examined the difficulties encountered when interacting with search interfaces via speech-based screen readers. In this article, we use our previous findings to inform the design of a search interface to support visually impaired users for complex information seeking. We particularly focus on implementing TrailNote, a tool to support visually impaired searchers in managing the search process, and we also redesign the spelling-support mechanism using nonspeech sounds to address previously observed difficulties in interacting with this feature. To enhance the user experience, we have designed interface features to be technically accessible as well as usable with speech-based screen readers. We have evaluated the proposed interface with 12 visually impaired users and studied how they interacted with the interface components. Our findings show that the search interface was effective in supporting participants for complex information seeking and that the proposed interface features were accessible and usable with speech-based screen readers.

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Abstract

This study investigated how people comprehend three-dimensional (3D) visualizations and what properties of such visualizations affect comprehension. Participants were asked to draw the face of a 3D visualization after it was cut in half. We videotaped the participants as they drew, erased, verbalized their thoughts, gestured, and moved about a two-dimensional paper presentation of the 3D visualization. The videorecords were analyzed using a grounded theory approach to generate hypotheses related to comprehension difficulties and visualization properties. Our analysis of the results uncovered three properties that made problem solving more difficult for participants. These were: (a) cuts that were at an angle in relation to at least one plane of reference, (b) nonplanar properties of the features contained in the 3D visualizations including curved layers and v-shaped layers, and (c) mixed combinations of layers. In contrast, (a) cutting planes that were perpendicular or parallel to the 3D visualization diagram's planes of reference, (b) internal features that were flat/planar, and (c) homogeneous layers were easier to comprehend. This research has direct implications for the generation and use of 3D information visualizations in that it suggests design features to include and avoid.

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Abstract

The scientific community's growing eagerness to make research data available to the public provides libraries - with our expertise in metadata and discovery - an interesting new opportunity. This paper details the in-house creation of a "data catalog" which describes datasets ranging from population-level studies like the US Census to small, specialized datasets created by researchers at our own institution. Based on Symfony2 and Solr, the data catalog provides a powerful search interface to help researchers locate the data that can help them, and an administrative interface so librarians can add, edit, and manage metadata elements at will. This paper will outline the successes, failures, and total redos that culminated in the current manifestation of our data catalog.

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Abstract

Icon system could represent an efficient solution for collective iconic categorization of knowledge by providing graphical interpretation. Their pictorial characters assist visualizing the structure of text to become more understandable beyond vocabulary obstacle. In this paper we are proposing a Knowledge Engineering (KM) based iconic representation approach. We assume that these systematic icons improve collective knowledge management. Meanwhile, text (constructed under our knowledge management model - Hypertopic) helps to reduce the diversity of graphical understanding belonging to different users. This "position paper" also prepares to demonstrate our hypothesis by an "iconic social tagging" experiment which is to be accomplished in 2011 with UTT students. We describe the "socio semantic web" information portal involved in this project, and a part of the icons already designed for this experiment in Sustainability field. We have reviewed existing theoretical works on icons from various origins, which can be used to lay the foundation of robust "icons systems".

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Abstract

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.

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Source

Re:inventing information science in the networked society: Proceedings of the 14th International Symposium on Information Science, Zadar/Croatia, 19th-21st May 2015. Eds.: F. Pehar, C. Schloegl u. C. Wolff

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Abstract

Automated methods for the analysis, modeling, and visualization of large-scale scientometric data provide measures that enable the depiction of the state of world scientific development. We aimed to integrate minimum span clustering (MSC) and minimum spanning tree methods to cluster and visualize the global pattern of scientific publications (PSP) by analyzing aggregated Science Citation Index (SCI) data from 1994 to 2011. We hypothesized that PSP clustering is mainly affected by countries' geographic location, ethnicity, and level of economic development, as indicated in previous studies. Our results showed that the 100 countries with the highest rates of publications were decomposed into 12 PSP groups and that countries within a group tended to be geographically proximal, ethnically similar, or comparable in terms of economic status. Hubs and bridging nodes in each knowledge production group were identified. The performance of each group was evaluated across 16 knowledge domains based on their specialization, volume of publications, and relative impact. Awareness of the strengths and weaknesses of each group in various knowledge domains may have useful applications for examining scientific policies, adjusting the allocation of resources, and promoting international collaboration for future developments.

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Abstract

Whereas traditional science maps emphasize citation statistics and static relationships, this paper presents a term-based method to identify and visualize the evolutionary pathways of scientific topics in a series of time slices. First, we create a data preprocessing model for accurate term cleaning, consolidating, and clustering. Then we construct a simulated data streaming function and introduce a learning process to train a relationship identification function to adapt to changing environments in real time, where relationships of topic evolution, fusion, death, and novelty are identified. The main result of the method is a map of scientific evolutionary pathways. The visual routines provide a way to indicate the interactions among scientific subjects and a version in a series of time slices helps further illustrate such evolutionary pathways in detail. The detailed outline offers sufficient statistical information to delve into scientific topics and routines and then helps address meaningful insights with the assistance of expert knowledge. This empirical study focuses on scientific proposals granted by the United States National Science Foundation, and demonstrates the feasibility and reliability. Our method could be widely applied to a range of science, technology, and innovation policy research, and offer insight into the evolutionary pathways of scientific activities.

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Abstract

Data from multiple knowledge organization systems are combined to provide a global overview of the content holdings of a small personal library. Subject headings and classification data are used to effectively map the combined book and topic space of the library. While harvested and manipulated by hand, the work reveals issues and potential solutions when using automated techniques to produce topic maps of much larger libraries. The small library visualized consists of the thirty-nine, digital, English language books found in the Osama Bin Laden (OBL) compound in Abbottabad, Pakistan upon his death. As this list of books has garnered considerable media attention, it is worth providing a visual overview of the subject content of these books - some of which is not readily apparent from the titles. Metadata from subject headings and classification numbers was combined to create book-subject maps. Tree maps of the classification data were also produced. The books contain 328 subject headings. In order to enhance the base map with meaningful thematic overlay, library holding count data was also harvested (and aggregated from duplicates). This additional data revealed the relative scarcity or popularity of individual books.

Content

Beitrag bei: NASKO 2017: Visualizing Knowledge Organization: Bringing Focus to Abstract Realities. The sixth North American Symposium on Knowledge Organization (NASKO 2017), June 15-16, 2017, in Champaign, IL, USA.

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Abstract

Map-based visualizations of document collections have become popular in recent times. However, most of these visualizations emphasize only geospatial properties of objects, leaving out other ontological properties. In this paper we propose to extend these visualizations to include nongeospatial properties of documents to support users with elementary and synoptic visual tasks. More specifically, additional suitable representations that can enhance the utility of map-based visualizations are discussed. To demonstrate the utility of the proposed solution, we have developed a prototype map-based visualization system using Google Maps (GM), which demonstrates how additional representations can be beneficial.

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Abstract

Complex cognitive activities, such as analytical reasoning, problem solving, and sense making, are often performed through the mediation of interactive computational tools. Examples include visual analytics, decision support, and educational tools. Through interaction with visual representations of information at the visual interface of these tools, a joint, coordinated cognitive system is formed. This partnership results in a number of relational properties-those depending on both humans and tools-that researchers and designers must be aware of if such tools are to effectively support the performance of complex cognitive activities. This article presents 10 properties of interactive visual representations that are essential and relational and whose values can be adjusted through interaction. By adjusting the values of these properties, better coordination between humans and tools can be effected, leading to higher quality performance of complex cognitive activities. This article examines how the values of these properties affect cognitive processing and visual reasoning and demonstrates the necessity of making their values adjustable-all of which is situated within a broader theoretical framework concerned with human-information interaction in complex cognitive activities. This framework can facilitate systematic research, design, and evaluation in numerous fields including information visualization, health informatics, visual analytics, and educational technology.

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Abstract

The authors of this paper investigate terms of consumers' diabetes based on a log from the Yahoo!Answers social question and answers (Q&A) forum, ascertain characteristics and relationships among terms related to diabetes from the consumers' perspective, and reveal users' diabetes information seeking patterns. In this study, the log analysis method, data coding method, and visualization multiple-dimensional scaling analysis method were used for analysis. The visual analyses were conducted at two levels: terms analysis within a category and category analysis among the categories in the schema. The findings show that the average number of words per question was 128.63, the average number of sentences per question was 8.23, the average number of words per response was 254.83, and the average number of sentences per response was 16.01. There were 12 categories (Cause & Pathophysiology, Sign & Symptom, Diagnosis & Test, Organ & Body Part, Complication & Related Disease, Medication, Treatment, Education & Info Resource, Affect, Social & Culture, Lifestyle, and Nutrient) in the diabetes related schema which emerged from the data coding analysis. The analyses at the two levels show that terms and categories were clustered and patterns were revealed. Future research directions are also included.

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Abstract

Purpose - Despite the importance of bibliographic information systems for discovering and exploring library resources, some of the core functionality that should be provided to support users in their information seeking process is still missing. Investigating these issues, the purpose of this paper is to design a solution that would fulfil the missing objectives. Design/methodology/approach - Building on the concepts of a work family, functional requirements for bibliographic records (FRBR) and information visualization, the paper proposes a model and user interface design that could support a more efficient and user-friendly presentation and navigation in bibliographic information systems. Findings - The proposed design brings together all versions of a work, related works, and other works by and about the author and shows how the model was implemented into a FrbrVis prototype system using hierarchical visualization layout. Research limitations/implications - Although issues related to discovery and exploration apply to various material types, the research first focused on works of fiction and was also limited by the selected sample of records. Practical implications - The model for presenting and interacting with FRBR-based data can serve as a good starting point for future developments and implementations. Originality/value - With FRBR concepts being gradually integrated into cataloguing rules, formats, and various bibliographic services, one of the important questions that has not really been investigated and studied is how the new type of data would be presented to users in a way that would exploit the true potential of the changes.

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Abstract

Topic models have been shown to be a useful way of representing the content of large document collections, for example, via visualization interfaces (topic browsers). These systems enable users to explore collections by way of latent topics. A standard way to represent a topic is using a term list; that is the top-n words with highest conditional probability within the topic. Other topic representations such as textual and image labels also have been proposed. However, there has been no comparison of these alternative representations. In this article, we compare 3 different topic representations in a document retrieval task. Participants were asked to retrieve relevant documents based on predefined queries within a fixed time limit, presenting topics in one of the following modalities: (a) lists of terms, (b) textual phrase labels, and (c) image labels. Results show that textual labels are easier for users to interpret than are term lists and image labels. Moreover, the precision of retrieved documents for textual and image labels is comparable to the precision achieved by representing topics using term lists, demonstrating that labeling methods are an effective alternative topic representation.

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Abstract

In the information science literature, recent studies have used patent databases and patent classification information to construct network maps of patent technology classes. In such a patent technology map, almost all pairs of technology classes are connected, whereas most of the connections between them are extremely weak. This observation suggests the possibility of filtering the patent network map by removing weak links. However, removing links may reduce the explanatory power of the network on inventor or organization diversification. The network links may explain the patent portfolio diversification paths of inventors and inventing organizations. We measure the diversification explanatory power of the patent network map, and present a method to objectively choose an optimal tradeoff between explanatory power and removing weak links. We show that this method can remove a degree of arbitrariness compared with previous filtering methods based on arbitrary thresholds, and also identify previous filtering methods that created filters outside the optimal tradeoff. The filtered map aims to aid in network visualization analyses of the technological diversification of inventors, organizations, and other innovation agents, and potential foresight analysis. Such applications to a prolific inventor (Leonard Forbes) and company (Google) are demonstrated.

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Abstract

Many successful digital interfaces employ visual metaphors to convey features or data properties to users, but the characteristics that make a visual metaphor effective are not well understood. We used a theoretical conception of metaphor from cognitive linguistics to design an interactive system for viewing the citation network of the corpora of literature in the JSTOR database, a highly connected compound graph of 2 million papers linked by 8 million citations. We created 4 variants of this system, manipulating 2 distinct properties of metaphor. We conducted a between-subjects experimental study with 80 participants to compare understanding and engagement when working with each version. We found that building on known image schemas improved response time on look-up tasks, while contextual detail predicted increases in persistence and the number of inferences drawn from the data. Schema-congruency combined with contextual detail produced the highest gains in comprehension. These findings provide concrete mechanisms by which designers presenting large data sets through metaphorical interfaces may improve their effectiveness and appeal with users.

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Abstract

Using Google Earth, Google Maps, and/or network visualization programs such as Pajek, one can overlay the network of relations among addresses in scientific publications onto the geographic map. The authors discuss the pros and cons of various options, and provide software (freeware) for bridging existing gaps between the Science Citation Indices (Thomson Reuters) and Scopus (Elsevier), on the one hand, and these various visualization tools on the other. At the level of city names, the global map can be drawn reliably on the basis of the available address information. At the level of the names of organizations and institutes, there are problems of unification both in the ISI databases and with Scopus. Pajek enables a combination of visualization and statistical analysis, whereas the Google Maps and its derivatives provide superior tools on the Internet.

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Abstract

Grounded on real industrial use cases, we recently proposed an ontology-based visual query system for SPARQL, named OptiqueVQS. Ontology-based visual query systems employ ontologies and visual representations to depict the domain of interest and queries, and are promising to enable end users without any technical background to access data on their own. However, even with considerably small ontologies, the number of ontology elements to choose from increases drastically, and hence hinders usability. Therefore, in this paper, we propose a method using the log of past queries for ranking and suggesting query extensions as a user types a query, and identify emerging issues to be addressed.

Series

Communications in computer and information science; 478

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Abstract

Visualization of scientific results using networks has become popular in scientometric research. We provide base maps for Mendeley reader count data using the publication year 2012 from the Web of Science data. Example networks are shown and explained. The reader can use our base maps to visualize other results with the VOSViewer. The proposed overlay maps are able to show the impact of publications in terms of readership data. The advantage of using our base maps is that it is not necessary for the user to produce a network based on all data (e.g., from 1 year), but can collect the Mendeley data for a single institution (or journals, topics) and can match them with our already produced information. Generation of such large-scale networks is still a demanding task despite the available computer power and digital data availability. Therefore, it is very useful to have base maps and create the network with the overlay technique.

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Abstract

In this article, we propose a graph-based interactive bibliographic information retrieval system-GIBIR. GIBIR provides an effective way to retrieve bibliographic information. The system represents bibliographic information as networks and provides a form-based query interface. Users can develop their queries interactively by referencing the system-generated graph queries. Complex queries such as "papers on information retrieval, which were cited by John's papers that had been presented in SIGIR" can be effectively answered by the system. We evaluate the proposed system by developing another relational database-based bibliographic information retrieval system with the same interface and functions. Experiment results show that the proposed system executes the same queries much faster than the relational database-based system, and on average, our system reduced the execution time by 72% (for 3-node query), 89% (for 4-node query), and 99% (for 5-node query).