Search (8 results, page 1 of 1)

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Abstract

This papers presents adaptations and tests undertaken to allow an information retrieval (IR) system to forecast the likelihood of avalanches on a particular day. The forecasting process uses historical data of the weather and avalanche condiditons for a large number of days. A method for adapting these data into a form usable by a text-based IR system is first described, followed by tests showing the resulting system's accuracy to be equal to existing 'custom built' forecasting systems. From this, it is concluded that the adaptation methodology id effective at allowing such data to be used in a text-based IR system. A number of advantages in using an IR system for avalanche forecasting are also presented

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Abstract

We analyze 18- million rows of Wi-Fi access logs collected over a 1-year period from over 120,000 anonymized users at an inner city shopping mall. The anonymized data set gathered from an opt-in system provides users' approximate physical location as well as web browsing and some search history. Such data provide a unique opportunity to analyze the interaction between people's behavior in physical retail spaces and their web behavior, serving as a proxy to their information needs. We found that (a) there is a weekly periodicity in users' visits to the mall; (b) people tend to visit similar mall locations and web content during their repeated visits to the mall; (c) around 60% of registered Wi-Fi users actively browse the web, and around 10% of them use Wi-Fi for accessing web search engines; (d) people are likely to spend a relatively constant amount of time browsing the web while the duration of their visit may vary; (e) the physical spatial context has a small, but significant, influence on the web content that indoor users browse; and (f) accompanying users tend to access resources from the same web domains.

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Abstract

A means of automatically deriving a hierarchical organization of concepts from a set of documents without use of training data or standard clustering techniques is presented. Using a process that extracts salient words and phrases from the documents, these terms are organized hierarchically using a type of co-occurrence known as subsumption. The resulting structure is displayed as a series of hierarchical menus. When generated from a set of retrieved documents, a user browsing the menus gains an overview of their content in a manner distinct from existing techniques. The methods used to build the structure are simple and appear to be effective. The formation and presentation of the hierarchy is described along with a study of some of its properties, including a preliminary experiment, which indicates that users may find the hierarchy a more efficient means of locating relevant documents than the classic method of scanning a ranked document list

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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

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

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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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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Date

26. 1.2014 18:48:22