Search (6 results, page 1 of 1)

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Source

Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon

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Abstract

The question of which type of computer science (CS) publication-conference or journal-is likely to result in more citations for a published paper is addressed. A series of data sets are examined and joined in order to analyze the citations of over 195,000 conference papers and 108,000 journal papers. Two means of evaluating the citations of journals and conferences are explored: h5 and average citations per paper; it was found that h5 has certain biases that make it a difficult measure to use (despite it being the main measure used by Google Scholar). Results from the analysis show that CS, as a discipline, values conferences as a publication venue more highly than any other academic field of study. The analysis also shows that a small number of elite CS conferences have the highest average paper citation rate of any publication type, although overall, citation rates in conferences are no higher than in journals. It is also shown that the length of a paper is correlated with citation rate.

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Abstract

A brief communication appearing in this journal ranked UK-based LIS and (some) IR academics by their h-index using data derived from the Thomson ISI Web of Science(TM) (WoS). In this brief communication, the same academics were re-ranked, using other popular citation databases. It was found that for academics who publish more in computer science forums, their h was significantly different due to highly cited papers missed by WoS; consequently, their rank changed substantially. The study was widened to a broader set of UK-based LIS and IR academics in which results showed similar statistically significant differences. A variant of h, hmx, was introduced that allowed a ranking of the academics using all citation databases together.

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Abstract

Finding a place of interest (e.g., a restaurant, hotel, or attraction) is often related to a group information need, however, the actual multiparty collaboration in such searches has not been explored, and little is known about its significance and related practices. We surveyed 100 computer science students and found that 94% (of respondents) searched for places online; 87% had done so as part of a group. Search for place by multiple active participants was experienced by 78%, with group sizes typically being 2 or 3. Search occurred in a range of settings with both desktop PCs and mobile devices. Difficulties were reported with coordinating tasks, sharing results, and making decisions. The results show that finding a place of interest is a quite different group-based search than other multiparty information-seeking activities. The results suggest that local search systems, their interfaces and the devices that access them can be made more usable for collaborative search if they include support for coordination, sharing of results, and decision making.

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Abstract

Folder navigation is the main way that personal computer users retrieve their own files. People dedicate considerable time to creating systematic structures to facilitate such retrieval. Despite the prevalence of both manual organization and navigation, there is very little systematic data about how people actually carry out navigation, or about the relation between organization structure and retrieval parameters. The aims of our research were therefore to study users' folder structure, personal file navigation, and the relations between them. We asked 296 participants to retrieve 1,131 of their active files and analyzed each of the 5,035 navigation steps in these retrievals. Folder structures were found to be shallow (files were retrieved from mean depth of 2.86 folders), with small folders (a mean of 11.82 files per folder) containing many subfolders (M=10.64). Navigation was largely successful and efficient with participants successfully accessing 94% of their files and taking 14.76 seconds to do this on average. Retrieval time and success depended on folder size and depth. We therefore found the users' decision to avoid both deep structure and large folders to be adaptive. Finally, we used a predictive model to formulate the effect of folder depth and folder size on retrieval time, and suggested an optimization point in this trade-off.

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Date

26. 1.2014 18:48:22