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281
Eigentaste: A Constant Time Collaborative Filtering Algorithm
, 2000
"... Eigentaste is a collaborative filtering algorithm that uses universal queries to elicit real-valued user ratings on a common set of items and applies principal component analysis (PCA) to the resulting dense subset of the ratings matrix. PCA facilitates dimensionality reduction for offline clusterin ..."
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Cited by 378 (6 self)
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, an online joke recommending system. Jester has collected approximately 2,500,000 ratings from 57,000 users. We use the Normalized Mean Absolute Error (NMAE) measure to compare performance of different algorithms. In the Appendix we use Uniform and Normal distribution models to derive analytic estimates
Meme-tracking and the Dynamics of the News Cycle
, 2009
"... Tracking new topics, ideas, and “memes” across the Web has been an issue of considerable interest. Recent work has developed methods for tracking topic shifts over long time scales, as well as abrupt spikes in the appearance of particular named entities. However, these approaches are less well suite ..."
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Cited by 363 (15 self)
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in the news media that have long been the subject of qualitative interpretation but have never been captured accurately enough to permit actual quantitative analysis. We tracked 1.6 million mainstream media sites and blogs over a period of three months with the total of 90 million articles and we find a set
Modeling Users ’ Adoption Behaviors with Social Selection and Influence∗
"... Massive users ’ online adoption behaviors were recorded thanks to the various emerging web services such as Facebook, Twitter, G+, Netflix and so on. Two key fac-tors that affect users ’ adoption behaviors are social selection and social influence. Understanding such factors underly-ing each behavio ..."
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behavior can potentially help web service providers gain much more insights into their users and improve pre-dictive power. In this paper, we try to answer (1) How do the roles of selection and influence play in a user-level adop-tion? (2) Capturing those factors can benefit the modeling and prediction
PROMISE - Modeling and Predicting User Query Behavior in Online Analytical Processing Environments
, 2000
"... . Users of Online Analytical Processing (OLAP) tools interactively analyze data that is struc- tured according to the multidimensional data model. The user's navigational query behavior in these environments often follows characteristic patterns mirroring the structure of the analytical proce ..."
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Cited by 3 (1 self)
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motivates this approach by presenting results of an analysis of the user behavior in a real-world OLAP environment. Further contributions of this paper are a model for characteristic OLAP query patterns based on Markov Models and a corresponding OLAP query prediction algorithm. 1 Introduction Online
Perspective An Online Bioinformatics Curriculum
"... Abstract: Online learning initia-tives over the past decade have become increasingly comprehen-sive in their selection of courses and sophisticated in their presen-tation, culminating in the recent announcement of a number of consortium and startup activities that promise to make a university educat ..."
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Abstract: Online learning initia-tives over the past decade have become increasingly comprehen-sive in their selection of courses and sophisticated in their presen-tation, culminating in the recent announcement of a number of consortium and startup activities that promise to make a university
Graphical Tools for Quantitative Radiology.
"... We will demonstrate a number of graphical tools for interactive analysis of multichannel images, such as those arising in MRI or PET. The basic idea that underlies all the tools is to provide (1) multiple graphical representations of the data from a given multichannel image and (2) linking mechanism ..."
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mechanisms that allow the user to see correspondences between the parts of the different views of the same data. We believe that these tools will become essential components of data analysis environments for quantitative radiology. In particular, we will show how these graphical tools can be used to study
On-line retrainable neural networks: improving the performance of neural networks in image analysis problems
- IEEE Trans. Neural Networks
, 2000
"... Abstract—A novel approach is presented in this paper for improving the performance of neural-network classifiers in image recognition, segmentation, or coding applications, based on a retraining procedure at the user level. The procedure includes: 1) a training algorithm for adapting the network wei ..."
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Cited by 49 (32 self)
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weights to the current condition; 2) a maximum a posteriori (MAP) estimation procedure for optimally selecting the most representative data of the current environment as retraining data; and 3) a decision mechanism for determining when network retraining should be activated. The training algorithm takes
A Realistic Model to Evaluate Routing Algorithms in the Internet
- in the Internet, Globecom 2001
"... This paper addresses the problem of evaluating routing algorithms via simulation in packet-switched networks when elastic traffic is involved. It highlights some deficiencies of classic approaches that fail to capture both the complex interactions of connections traversing multiple bottlenecks and c ..."
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Cited by 10 (9 self)
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this analysis it is clear that quantitative and also qualitative behaviors of dynamic routing algorithms based on traffic measurements may be fairly different depending on the nature of the traffic loading the network, as well as depending on its interactions with the network parameters and behavior.
Online Video Promotion with User Specific Information
"... ABSTRACT: There are various ways and methods used in video recommendation which are purely statistical. These would give recommendations to users based on either their previous search or other criteria. These systems set up a large number of context collectors at the terminals. However, the context ..."
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of the system for user satisfaction. KEYWORDS: Spammer ,User created content, Video-Tag , private storage, recommender. I.INTRODUCTION Online video sharing systems, out of which YouTube[1] is the most popular, provide features that allow users to post a video as a response to a discussion topic. These features
Dynamics and generalization ability of LVQ algorithms
- Journal of Machine Learning Research
, 2006
"... Learning vector quantization (LVQ) schemes constitute intuitive, powerful classification heuristics with numerous successful applications but, so far, limited theoretical background. We study LVQ rigorously within a simplifying model situation: two competing prototypes are trained from a sequence of ..."
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Cited by 29 (16 self)
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abilities. This is also possible for heuristic training schemes which do not relate to a cost function. We compare the performance of several algorithms, including Kohonen’s LVQ1 and LVQ+/-, a limiting case of LVQ2.1. The former shows close to optimal performance, while LVQ+/- displays divergent behavior
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