Evaluating tag-based information access in image collections

The availability of social tags has greatly enhanced access to information. Tag clouds have emerged as a new "social" way to find and visualize information, providing both one-click access to information and a snapshot of the "aboutness" of a tagged collection. A range of research projects explored and compared different tag artifacts for information access ranging from regular tag clouds to tag hierarchies. At the same time, there is a lack of user studies that compare the effectiveness of different types of tag-based browsing interfaces from the users point of view. This paper contributes to the research on tag-based information access by presenting a controlled user study that compared three types of tag-based interfaces on two recognized types of search tasks - lookup and exploratory search. Our results demonstrate that tag-based browsing interfaces significantly outperform traditional search interfaces in both performance and user satisfaction. At the same time, the differences between the two types of tag-based browsing interfaces explored in our study are not as clear. Copyright 2012 ACM

Tag-Cloud Drawing: Algorithms for Cloud Visualization

Tag clouds provide an aggregate of tag-usage statistics. They are typically sent as in-line HTML to browsers. However, display mechanisms suited for ordinary text are not ideal for tags, because font sizes may vary widely on a line. As well, the typical layout does not account for relationships that may be known between tags. This paper presents models and algorithms to improve the display of tag clouds that consist of in-line HTML, as well as algorithms that use nested tables to achieve a more general 2-dimensional layout in which tag relationships are considered. The first algorithms leverage prior work in typesetting and rectangle packing, whereas the second group of algorithms leverage prior work in Electronic Design Automation. Experiments show our algorithms can be efficiently implemented and perform well.Comment: To appear in proceedings of Tagging and Metadata for Social Information Organization (WWW 2007

Txt2vz: a new tool for generating graph clouds

We present txt2vz (txt2vz.appspot.com), a new tool for automatically generating a visual summary of unstructured text data found in documents or web sites. The main purpose of the tool is to give the user information about the text so that they can quickly get a good idea about the topics covered. Txt2vz is able to identify important concepts from unstructured text data and to reveal relationships between those concepts. We discuss other approaches to generating diagrams from text and highlight the differences between tag clouds, word clouds, tree clouds and graph clouds

Interactive tag maps and tag clouds for the multiscale exploration of large spatio-temporal datasets

'Tag clouds' and 'tag maps' are introduced to represent geographically referenced text. In combination, these aspatial and spatial views are used to explore a large structured spatio-temporal data set by providing overviews and filtering by text and geography. Prototypes are implemented using freely available technologies including Google Earth and Yahoo! 's Tag Map applet. The interactive tag map and tag cloud techniques and the rapid prototyping method used are informally evaluated through successes and limitations encountered. Preliminary evaluation suggests that the techniques may be useful for generating insights when visualizing large data sets containing geo-referenced text strings. The rapid prototyping approach enabled the technique to be developed and evaluated, leading to geovisualization through which a number of ideas were generated. Limitations of this approach are reflected upon. Tag placement, generalisation and prominence at different scales are issues which have come to light in this study that warrant further work

Collaborative OLAP with Tag Clouds: Web 2.0 OLAP Formalism and Experimental Evaluation

Increasingly, business projects are ephemeral. New Business Intelligence tools must support ad-lib data sources and quick perusal. Meanwhile, tag clouds are a popular community-driven visualization technique. Hence, we investigate tag-cloud views with support for OLAP operations such as roll-ups, slices, dices, clustering, and drill-downs. As a case study, we implemented an application where users can upload data and immediately navigate through its ad hoc dimensions. To support social networking, views can be easily shared and embedded in other Web sites. Algorithmically, our tag-cloud views are approximate range top-k queries over spontaneous data cubes. We present experimental evidence that iceberg cuboids provide adequate online approximations. We benchmark several browser-oblivious tag-cloud layout optimizations.Comment: Software at https://github.com/lemire/OLAPTagClou

Tag clouds for situated interaction and place profiling

Tag clouds have become very popular as visual representations of the main topics in document sets or as navigation tools that can provide quick access to resources related with specific topics. However, their ability to represent the information environment associated with any meaningful reality in a way that is collectively visible, actionable and easily understood may also be very relevant, even when the reality being represented is no longer a set of documents or resources, but a stream of interactions occurring within a particular ubiquitous computing environment. In this paper, we explore the use of tag clouds within the context of situated displays and services. We hypothesise that such tag clouds may have a role as dynamic representations of place and also as interaction controls, supporting the same comprehension and navigation functions of classical tag clouds. We describe two case studies in which this concept of situated tag cloud has been experimented in real-world settings. The case studies demonstrate two different applications of the tag cloud concept as the basis for place description and situated interaction. The results obtained from the case studies suggest that situated tag clouds can indeed provide valuable representations of place and situations and can also support simple interaction models, allowing people to reason about the system behaviour and how it is being influenced by new interactions.Fernando Ribeiro was supported by a Portuguese Foundation for Science and Technology scholarship (SFRH/BD/31292/2006). The research leading to these results has received funding from FCT under the Carnegie Mellon - Portugal agreement: Wesp (Web Security and Privacy (Grant CMU-PT/SE/028/2008)

Relevant clouds: leveraging relevance feedback to build tag clouds for image search

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-40802-1_18Previous work in the literature has been aimed at exploring tag clouds to improve image search and potentially increase retrieval performance. However, to date none has considered the idea of building tag clouds derived from relevance feedback. We propose a simple approach to such an idea, where the tag cloud gives more importance to the words from the relevant images than the non-relevant ones. A preliminary study with 164 queries inspected by 14 participants over a 30M dataset of automatically annotated images showed that 1) tag clouds derived this way are found to be informative: users considered roughly 20% of the presented tags to be relevant for any query at any time; and 2) the importance given to the tags correlates with user judgments: tags ranked in the first positions tended to be perceived more often as relevant to the topic that users had in mind.Work supported by EU FP7/2007-2013 under grant agreements 600707 (tranScriptorium) and 287576 (CasMaCat), and by the STraDA project (TIN2012-37475-C02-01).Leiva Torres, LA.; Villegas Santamaría, M.; Paredes Palacios, R. (2013). Relevant clouds: leveraging relevance feedback to build tag clouds for image search. En Information Access Evaluation. Multilinguality, Multimodality, and Visualization. Springer Verlag (Germany). 143-149. https://doi.org/10.1007/978-3-642-40802-1_18S143149Begelman, G., Keller, P., Smadja, F.: Automated tag clustering: Improving search and exploration in the tag space. In: Collaborative Web Tagging (2006)Callegari, J., Morreale, P.: Assessment of the utility of tag clouds for faster image retrieval. In: Proc. MIR (2010)Ganchev, K., Hall, K., McDonald, R., Petrov, S.: Using search-logs to improve query tagging. In: Proc. ACL (2012)Hassan-Montero, Y., Herrero-Solana, V.: Improving tag-clouds as visual information retrieval interfaces. In: Proc. InSciT (2006)Leiva, L.A., Villegas, M., Paredes, R.: Query refinement suggestion in multimodal interactive image retrieval. In: Proc. ICMI (2011)Liu, D., Hua, X.-S., Yang, L., Wang, M., Zhang, H.-J.: Tag ranking. In: Proc. WWW (2009)Overell, S., Sigurbjörnsson, B., van Zwol, R.: Classifying tags using open content resources. In: Proc. WSDM (2009)Rui, Y., Huang, T.S., Ortega, M., Mehrotra, S.: Relevance feedback: A power tool for interactive content-based image retrieval. T. Circ. Syst. Vid. 8(5) (1998)Sigurbjörnsson, B., van Zwol, R.: Flickr tag recommendation based on collective knowledge. In: Proc. WWW (2008)Trattner, C., Lin, Y.-L., Parra, D., Yue, Z., Real, W., Brusilovsky, P.: Evaluating tag-based information access in image collections. In: Proc. HT (2012)Villegas, M., Paredes, R.: Image-text dataset generation for image annotation and retrieval. In: Proc. CERI (2012)Zhang, C., Chai, J.Y., Jin, R.: User term feedback in interactive text-based image retrieval. In: Proc. SIGIR (2005

Toward a better understanding of viewers' perceptions of tag clouds : relative size judgment

This dissertation focuses on viewers' perception of the relative size of words presented in tag clouds. A tag cloud is a representation of the word content of a source document where the relative frequency, or importance, of the keywords (i.e., tags) is depicted by presenting the most important tag words in a cluster called a tag cloud and varying visual characteristics of the tag words such as color, saturation, location and size. Although previous research has found that relative size is a strong visual factor for communicating relative importance of tag words, it is still unclear how viewers perceive the relative size of the words in tag clouds and how perceived size is influenced by other tag cloud characteristics. This dissertation looks at how viewers estimate the relative size of words given different characteristics such as decorations like (e.g., filled areas, boxes, and shadows), appearance of the words (e.g., varying the amount of narrow or wide letters), the typeface style (e.g., bold typeface), and location in the tag cloud (e.g., upper left vs. upper right quadrants). Significant under- and over-perception of the relative size of tag words were observed, primarily varying with the size of the target tag word. Word appearance had a modest effect on size misperception, while typeface style and location had a smaller effect. The results provide insight regarding the influence of surrounding tags on the perception of relative size of a tag word, as well as guidance to tag cloud designers regarding the influence of other presentation characteristics on perceived relative size