Visualizing Paths in Context

Data about movement through a space is increasingly becoming available for capture and analysis. In many applications, this data is captured or modeled as transitions between a small number of areas of interests, or a finite set of states, and these transitions constitute paths in the space. Similarities and differences between paths are of great importance to such analyses, but can be difficult to assess. In this work we present a visualization approach for representing paths in context, where individual paths can be compared to other paths or to a group of paths. Our approach summarizes path behavior using a simple circular layout, including information about state and transition likelihood using Markov random models, together with information about specific path and state behavior. The layout avoids line crossovers entirely, making it easy to observe patterns while reducing visual clutter. In our tool, paths can either be compared in their natural sequence or by aligning multiple paths using Multiple Sequence Alignment, which can better highlight path similarities. We applied our technique to eye tracking data and cell phone tower data used to capture human movement

Data-driven evaluation metrics for heterogeneous search engine result pages

Evaluation metrics for search typically assume items are homoge- neous. However, in the context of web search, this assumption does not hold. Modern search engine result pages (SERPs) are composed of a variety of item types (e.g., news, web, entity, etc.), and their influence on browsing behavior is largely unknown. In this paper, we perform a large-scale empirical analysis of pop- ular web search queries and investigate how different item types influence how people interact on SERPs. We then infer a user brows- ing model given people’s interactions with SERP items – creating a data-driven metric based on item type. We show that the proposed metric leads to more accurate estimates of: (1) total gain, (2) total time spent, and (3) stopping depth – without requiring extensive parameter tuning or a priori relevance information. These results suggest that item heterogeneity should be accounted for when de- veloping metrics for SERPs. While many open questions remain concerning the applicability and generalizability of data-driven metrics, they do serve as a formal mechanism to link observed user behaviors directly to how performance is measured. From this approach, we can draw new insights regarding the relationship be- tween behavior and performance – and design data-driven metrics based on real user behavior rather than using metrics reliant on some hypothesized model of user browsing behavior

A Graph-Based Approach towards Discerning Inherent Structures in a Digital Library of Formal Mathematics

As the amount of online formal mathematical content grows, for example through active efforts such as the Mathweb [21], MOWGLI [4], Formal Digital Library, or FDL [1], and others, it becomes increasingly valuable to find automated means to manage this data and capture semantics such as relatedness and significance. We apply graph-based approaches, such as HITS, or Hyperlink-Induced Topic Search, [11] used for World Wide Web document search and analysis, to formal mathematical data collections. The nodes of the graphs we analyze are theorems and definitions, and the links are logical dependencies. By exploiting this link structure, we show how one may extract organizational and relatedness information from a collection of digital formal math. We discuss the value of the information we can extract, yielding potential applications in math search tools, theorem proving, and education

Frequency and Structure of Long Distance Scholarly Collaborations in a Physics Community

The authors present results from a real-world study depicting remote collaboration trends of a community of more than 87,000 scientists over 30 years. They utilize publication records of more than 200,000 scholarly journal articles, together with affiliations of the authors to infer distance collaborations. The longevity of their study is of interest because it covers several years before and after the birth of the Internet and computer-supported collaborative work (CSCW) technologies. Thus, they provide one lens through which the impact of computerassisted collaborative work technologies can be viewed. Their results show that there has been a steady and constant growth in the frequency of both interinstitute and cross-country collaborations in a particular physics domain, regardless of the introduction of these technologies. This suggests that we are witnessing an evolution, rather than a revolution, with respect to long-distance collaborative behavior. An interdisciplinary approach, combining numerical statistics, graph visualizations, and social network measurements, facilitates their remarks on the changes in the size and structure of these collaborations over this period of history

Using Formal Reference to Enhance Authority and Integrity in Online Mathematical Texts

The amount and variety of digital information readily available to the public has become one of the defining features of the intellectual and scientific landscape. Digital information is bringing to the forefront new questions for computing and information science, e.g., how should this information be organized, searched, and evaluated. Universities, publishers, government, and other esteemed professionals bring unique and essential value to this enterprise that goes beyond their support of research – namely, intellectual authority. The imprimatur given to the information resources they own or sponsor is essential in helping individuals assess the validity of what they encounter on the Web. Recognizing quality online is important to creators and consumers of both open-access and peer-reviewed publications, digital libraries, newsgroups, and e-learning repositories. For example, one of the important ways in which the NSDL (National Science Digital Library) seeks to distinguish itself among digital libraries is by the authority of its collections. Also, the most respected journal publishers adhere to high standards and efforts to uphold the quality of their publications