1818817
An Exploratory Study on Knowledge Sharing in Information Retrieval
Different types of knowledge have been found important for a successful search. We designed a user interface: CIRR tool (Collaborative Information Retrieval Research) that supports sharing of search results as well as search queries (knowledge of finding the relevant items). We conducted a pilot study to explore what factors would affect the use of these knowledge sharing features. The results demonstrate that knowledge sharing in general is preferred by only some subjects for some tasks. For those who preferred sharing they share search queries, domain knowledge, and search results, rather than the usefulness judgment. The findings also show that knowledge sharing does not seem to have effects on search performance. However, it is significantly associated with the perceived task difficulty. The possible reasons leading to these results are analyzed. Limitations of this study are pointed out and the future studies are discussed.
62769950
Assessment of the effects of user characteristics on mental models of information retrieval systems
This article reports the results of a study that investigated effects of four user characteristics on users' mental models of information retrieval systems: educational and professional status, first language, academic background, and computer experience. The repertory grid technique was used in the study. Using this method, important components of information retrieval systems were represented by nine concepts, based on four IR experts' judgments. Users' mental models were represented by factor scores that were derived from users' matrices of concept ratings on different attributes of the concepts. The study found that educational and professional status, academic background, and computer experience had significant effects in differentiating users on their factor scores. First language had a borderline effect, but the effect was not significant enough at α = 0.05 level. Specific different views regarding IR systems among different groups of users are described and discussed. Implications of the study for information science and IR system designs are suggested.
37914154
Collaborative relevance judgment: A group consensus method for evaluating user search performance
Relevance judgment has traditionally been considered a personal and subjective matter. A user's search and the search result are treated as an isolated event. To consider the collaborative nature of information retrieval (IR) in a group/organization or even societal context, this article proposes a method that measures relevance based on group/peer consensus. The method can be used in IR experiments. In this method, the relevance of a document is decided by group consensus, or more specifically, by the number of users (or experiment participants) who retrieve it for the same search question. The more users who retrieve it, the more relevant the document will be considered. A user's search performance can be measured by a relevance score based on this notion. The article reports the results of an experiment using this method to compare the search performance of different types of users. Related issues with the method and future directions are also discussed.
14687114
Price Cycles in Online Advertising Auctions
Paid placement in search engines has become one of the most successful and rapidly growing sectors of the online advertising industry. The innovative use of auctions to sell keyword-related advertisement positions is perhaps the most important factor driving the success of this market. There has been no systematic analysis, however, of the advertisers’ strategies to bid for ranks in a dynamic environment, where each bidder’s bid can be updated and observed by the competitors in real time. We capture this dynamic setting using a Markov process and identify the Markov perfect equilibrium. We find that in such a dynamic environment, bidders’ bidding strategies follow a cyclical pattern (Edgeworth cycle) similar to that conjectured by Edgeworth (1925) in a totally different context. A new data set that contains a detailed bidding history of all advertisers for sample keywords in a leading search engine makes it possible for us to study the real-world behavior of bidders. We propose an empirical framework based on maximum likelihood estimation of latent Markov state switching to confirm the theory. We also discuss the theoretical and practical significance of finding such cycles in an online market place.
2953976
A performance study of monitoring and information services for distributed systems
Monitoring and information services form a key component of a distributed system, or Grid. A quantitative study of such services can aid in understanding the performance limitations, advise in the deployment of the monitoring system, and help evaluate future development work. To this end, we study the performance of three monitoring and information services for distributed systems: the Globus Toolkit/spl reg/ Monitoring and Discovery Service (MDS2), the European Data Grid Relational Grid Monitoring Architecture (R-GMA) and Hawkeye, part of the Condor project. We perform experiments to test their scalability with respect to number of users, number of resources and amount of data collected. Our study shows that each approach has different behaviors, often due to their different design goals. In the four sets of experiments we conducted to evaluate the performance of the service components under different circumstances, we found a strong advantage to caching or pre-fetching the data, as well as the need to have primary components at well-connected sites because of the high load seen by all systems.
6891881
Analysis of multimedia workloads with implications for internet streaming
In this paper, we study the media workload collected from a large number of commercial Web sites hosted by a major ISP and that collected from a large group of home users connected to the Internet via a well-known cable company. Some of our key findings are: (1) Surprisingly, the majority of media contents are still delivered via downloading from Web servers. (2) A substantial percentage of media downloading connections are aborted before completion due to the long waiting time. (3) A hybrid approach, pseudo streaming, is used by clients to imitate real streaming. (4) The mismatch between the downloading rate and the client playback speed in pseudo streaming is common, which either causes frequent playback delays to the clients, or unnecessary traffic to the Internet. (5) Compared with streaming, downloading and pseudo streaming are neither bandwidth efficient nor performance effective. To address this problem, we propose the design of AutoStream, an innovative system that can provide additional previewing and streaming services automatically for media objects hosted on standard Web sites in server farms at the client's will.
14511182
Does internet media traffic really follow Zipf-like distribution?
It is commonly agreed that Web traffic follows the Zipf-like distribution, which is an analytical foundation for improving Web access performance by client-server based proxy caching systems on the Internet. However, some recent studies have observed non-Zipf-like distributions of Internet media traffic in different content delivery systems. Due to the variety of media delivery systems and the diversity of media content, existing studies on media traffic are largely workload specific, and the observed access patterns are often different from or even conflict with each other. For Web media systems, study [3] reports that the access pattern of streaming media is Zipf-like in a university campus network, while study [2] finds that it is not Zipf-like in an enterprise media server. For VoD media systems, study [1] finds that it is not Zipf-like in a multicast-based Media-on-Demand server of a campus network, while study [9] reports it is Zipf-like in a large VoD streaming system of an ISP. For P2P media systems, study [4] reports that the access pattern of media workload in KaZaa system collected in a campus network is not Zipf-like, while study [5] reports that it is Zipf-like in another campus network. For live streaming media systems, study [8] reports it is Zipf-like while study [6] reports it is not Zipf-like. A number of models have been proposed to explain the observed media access patterns, such as the generalized Zipf-like model [7], “fetch-at-most-once” model [4], and two-mode Zipf model [6]. However, each of these models can only explain a very limited scope of measurement results. A general model of Internet media access patterns is highly desirable for traffic engineering on the Internet and is critical to design, benchmark, and evaluate Internet media delivery systems. In this study, we have analyzed a wide variety of media workloads on the Internet. The workloads were collected from both the client side and the server side in Web, VoD, P2P, and live streaming environments between 1998 and 2006, where the media content is delivered via Web/P2P downloading or unicast/multicast streaming. The duration of these workloads ranges from a few days to more than two years and the user population ranges from several thousands to more than one hundred thousand. The number of client requests
9689230
Doubly stochastic matrices of trees
Abstract In this paper, we obtain sharp upper and lower bounds for the smallest entries of doubly stochastic matrices of trees and characterize all extreme graphs which attain the bounds. We also present a counterexample to Merris’ conjecture on relations between the smallest entry of the doubly stochastic matrix and the algebraic connectivity of a graph in [R. Merris, Doubly stochastic graph matrices II, Linear Multilinear Algebr. 45 (1998) 275–285].