Search (13 results, page 1 of 1)

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Abstract

Describes the Reuters test collection, which at 22.173 references is significantly larger than most traditional test collections. In addition, Reuters has none of the recall calculation problems normally associated with some of the larger test collections available. Explains the method derived by D.D. Lewis to perform retrieval experiments on the Reuters collection and illustrates the use of the Reuters collection using some simple retrieval experiments that compare the performance of stemming algorithms

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

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

In this article the authors present Eurovision, a textbased system for cross-language (CL) image retrieval. The system is evaluated by multilingual users for two search tasks with the system configured in English and five other languages. To the authors' knowledge, this is the first published set of user experiments for CL image retrieval. They show that (a) it is possible to create a usable multilingual search engine using little knowledge of any language other than English, (b) categorizing images assists the user's search, and (c) there are differences in the way users search between the proposed search tasks. Based on the two search tasks and user feedback, they describe important aspects of any CL image retrieval system.

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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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Abstract

This brief communication describes the results of a questionnaire examining certain aspects of the Web-based information seeking practices of university students. The results are contrasted with past work showing that queries to Web search engines can be assigned to one of a series of categories: navigational, informational, and transactional. The survey results suggest that a large group of queries, which in the past would have been classified as informational, have become at least partially navigational. We contend that this change has occurred because of the rise of large Web sites holding particular types of information, such as Wikipedia and the Internet Movie Database.

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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

This study investigated a relatively unexamined query type, queries composed of URLs. The extent, variation, and user click-through behavior was examined to determine the intent behind URL queries. The study made use of a search log from which URL queries were identified and selected for both qualitative and quantitative analyses. It was found that URL queries accounted for ?17% of the sample. There were statistically significant differences between URL queries and non-URL queries in the following attributes: mean query length; mean number of tokens per query; and mean number of clicks per query. Users issuing such queries clicked on fewer result list items higher up the ranking compared to non-URL queries. Classification indicated that nearly 86% of queries were navigational in intent with informational and transactional queries representing about 7% of URL queries each. This is in contrast to past research that suggested that URL queries were 100% navigational. The conclusions of this study are that URL queries are relatively common and that simply returning the page that matches a user's URL is not an optimal strategy.

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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

We address the challenge of extracting query biased audio summaries from podcasts to support users in making relevance decisions in spoken document search via an audio-only communication channel. We performed a crowdsourced experiment that demonstrates that transcripts of spoken documents created using Automated Speech Recognition (ASR), even with significant errors, are effective sources of document summaries or "snippets" for supporting users in making relevance judgments against a query. In particular, the results show that summaries generated from ASR transcripts are comparable, in utility and user-judged preference, to spoken summaries generated from error-free manual transcripts of the same collection. We also observed that content-based audio summaries are at least as preferred as synthesized summaries obtained from manually curated metadata, such as title and description. We describe a methodology for constructing a new test collection, which we have made publicly available.

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Abstract

This research analyzes human-generated clarification questions to provide insights into how they are used to disambiguate and provide a better understanding of information needs. A set of clarification questions is extracted from posts on the Stack Exchange platform. Novel taxonomy is defined for the annotation of the questions and their responses. We investigate the clarification questions in terms of whether they add any information to the post (the initial question posted by the asker) and the accepted answer, which is the answer chosen by the asker. After identifying, which clarification questions are more useful, we investigated the characteristics of these questions in terms of their types and patterns. Non-useful clarification questions are identified, and their patterns are compared with useful clarifications. Our analysis indicates that the most useful clarification questions have similar patterns, regardless of topic. This research contributes to an understanding of clarification in conversations and can provide insight for clarification dialogues in conversational search scenarios and for the possible system generation of clarification requests in information-seeking conversations.

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Date

26. 1.2014 18:48:22

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Abstract

We examined whether the microblog comments given by people after reading a web document could be exploited to improve the accuracy of a web document summarization system. We examined the effect of social information (i.e., tweets) on the accuracy of the generated summaries by comparing the user preference for TBS (tweet-biased summary) with GS (generic summary). The result of crowdsourcing-based evaluation shows that the user preference for TBS was significantly higher than GS. We also took random samples of the documents to see the performance of summaries in a traditional evaluation using ROUGE, which, in general, TBS was also shown to be better than GS. We further analyzed the influence of the number of tweets pointed to a web document on summarization accuracy, finding a positive moderate correlation between the number of tweets pointed to a web document and the performance of generated TBS as measured by user preference. The results show that incorporating social information into the summary generation process can improve the accuracy of summary. The reason for people choosing one summary over another in a crowdsourcing-based evaluation is also presented in this article.