(c) ACM, 2011. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in 13th ACM International Conference on Ubiquitous Computing , 2011-09-01.
{Understanding utilization of city roads is important for urban planners. In this paper, we show how to use cellular hand- off patterns from cellular phone networks to identify which routes people take through a city. Specifically, this paper makes the following three contributions. First, we show that cellular handoff patterns on a given route are stable across a range of conditions and propose a way to measure stability within and between routes using a variant of Earth Mover�s Distance. Second, we present two accurate classification al- gorithms for matching cellular handoff patterns to routes: one requires test drives on the routes while the other uses signal strength data collected by high-resolution scanners. Finally, we present an application of our algorithms for mea- suring relative volumes of traffic on routes leading into and out of a specific city, and validate our methods using statis- tics published by a state transportation authority.}
The definitive version was published in PURBA-2011. , 2011-06-12
{Understanding the mix of different types of people in a city is an important input into urban planning. In this paper we identify distinct sectors of a population by their cellular phone usage. In a study of a small suburban city in New Jersey, we use unsupervised clustering to identify the usage patterns of heavy users . We uncover 7 unique usage patterns. We interpret two of the patterns as belonging to commuters and students, and verify these interpretations with deeper analysis of temporal and spatial patterns. }
The definitive version was published in IEEE Pervasive Computing , 2010-04-01, URL: https://ecopyright.ieee.org/ECTT/login.jsp Username: SCHPCSI-2011-01-0005 Password: 1295115660850
{The rapid growth of modern cities leaves urban planners faced with numerous challenges, such as high congestion and pollution levels. Effectively solving these challenges re- quires a deep understanding of existing city dynamics. In this paper, we describe methodology to study and monitor these dynamics by using Call Detail Records (CDRs), rou- tinely collected by wireless service providers as part of run- ning their networks. Our methodology scales to an entire population, has little additional cost, and can be continually updated. This provides an unprecedented opportunity to study and monitor cities in a way that current practices are not able to do.}
Methods And Apparatus For Modeling Relationships At Multiple Scales In Ratings Estimation,
Tue Jul 24 12:52:57 EDT 2012
Systems and techniques for generating item ratings for a user in order to allow for recommendations of selected items for that user. A set of known ratings of different items for a plurality of users is collected and maintained, and these known ratings are used to estimate rating factors influencing ratings, including user and item factors. Initial user and item factors are estimated and new user and item factors are successively added, with the original rating factors being progressively shrunk so as to reduce their magnitude and their contribution to the rating estimation as successive factors are added. When an appropriate number of user and item factors has been estimated, the rating factors are used to estimate ratings of items for a user, and the estimated ratings are employed to generate recommendations for that user.
Method And Apparatus For Measuring And Extracting Proximity In Networks,
Tue Nov 09 15:50:43 EST 2010
A method and apparatus for measuring and extracting proximity in networks are disclosed. In one embodiment, the present method receives a network from a user for analysis and extraction of a smaller proximity sub-graph. The method computes a candidate sub-graph and determines at least one Cycle Free Escape Conductivity (CFEC) proximity of at least two nodes in accordance with the candidate sub-graph. The method then extracts and presents a proximity sub-graph that best captures the proximity.
Method and system for squashing a large data set,
Tue Mar 25 18:08:39 EST 2003
Apparatus and method for summarizing an original large data set with a representative data set. The data elements in both the original data set and the representative data set have the same variables, but there are significantly fewer data elements in the representative data set. Each data element in the representative data set has an associated weight, representing the degree of compression. There are three steps for constructing the representative data set. First, the original data elements are partitioned into separate bins. Second, moments of the data elements partitioned in each bin are calculated. Finally, the representative data set is generated by finding data elements and associated weights having substantially the same moments as the original data set.