8468902
Segmentation and recognition of multi-attribute motion sequences
In this work, we focus on fast and efficient recognition of motions in multi-attribute continuous motion sequences. 3D motion capture data, animation motion data, and sensor data from gesture sensing devices are examples of multi-attribute continuous motion sequences. These sequences have multiple attributes rather than only one attribute as time series data has. Motions can have different rates and durations, and the resulting data can thus have different lengths. Also, motion data can have noises due to transitions between successive motions. Hence, traditional distance measuring approaches used for time series data (such as Euclidean distances or dynamic time-warped distances) are not suitable for recognition in multi-attribute motion sequences. Hence, we have defined a similarity measure based on the analysis of singular value decomposition (SVD) properties of similar multi-attribute motions. A five-phase algorithm has then been proposed that gives good pruning power by exploiting the proximity of continuous motion data. We experimented this algorithm with data from different sources: 3D motion capture devices, animation motions, and CyberGlove gesture sensing device. These experiments show that our algorithm can segment and recognize long motion streams with high accuracy and in real time without knowing beforehand the number of motions in a stream.
15797731
A Novel Indexing Approach for Efficient and Fast Similarity Search of Captured Motions
Indexing of motion data is important for quickly searching similar motions for sign language recognition and gait analysis and rehabilitation. This paper proposes a simple and efficient tree structure for indexing motion data with dozens of attributes. Feature vectors are extracted for indexing by using singular value decomposition (SVD) properties of motion data matrices. By having similar motions with large variations indexed together, searching for similar motions of a query needs only one node traversal at each tree level, and only one feature needs to be considered at one tree level. Experiments show that the majority of irrelevant motions can be pruned while retrieving all similar motions, and one traversal of the indexing tree takes only several microseconds with the existence of motion variations.
561187
Bilateral negotiation decisions with uncertain dynamic outside options
Negotiation is an important phase of e-contracting. E-contracting requires a proper negotiation model to effectively support negotiation decisions or automate the negotiation process. When an entity negotiates with a potential contractor, there may be some alternatives that exist simultaneously with the potential contractor, and/or some may present themselves in the future. We present a model for bilateral contract negotiations that considers the uncertain and dynamic outside options. Outside options affect the negotiation strategies via their impact on the reservation price. The model is composed of three modules, single-threaded negotiations, synchronized multi-threaded negotiations, and dynamic multi-threaded negotiations. These three models embody increased sophistication and complexity. The single-threaded negotiation model provides negotiation strategies without specifically considering outside options. The model of synchronized multi-threaded negotiations builds on the single-threaded negotiation model and considers the presence of concurrently existing outside options. The model of dynamic multi-threaded negotiations expands the synchronized multi-threaded model by considering the uncertain outside options that may come dynamically in the future. Experimental analysis is provided to characterize the impact of outside options on the negotiation strategy and performances.
6241358
Executing SQL over encrypted data in the database-service-provider model
Rapid advances in networking and Internet technologies have fueled the emergence of the "software as a service" model for enterprise computing. Successful examples of commercially viable software services include rent-a-spreadsheet, electronic mail services, general storage services, disaster protection services. "Database as a Service" model provides users power to create, store, modify, and retrieve data from anywhere in the world, as long as they have access to the Internet. It introduces several challenges, an important issue being data privacy. It is in this context that we specifically address the issue of data privacy.There are two main privacy issues. First, the owner of the data needs to be assured that the data stored on the service-provider site is protected against data thefts from outsiders. Second, data needs to be protected even from the service providers, if the providers themselves cannot be trusted. In this paper, we focus on the second challenge. Specifically, we explore techniques to execute SQL queries over encrypted data. Our strategy is to process as much of the query as possible at the service providers' site, without having to decrypt the data. Decryption and the remainder of the query processing are performed at the client site. The paper explores an algebraic framework to split the query to minimize the computation at the client site. Results of experiments validating our approach are also presented.
17199559
Data Mining for Direct Marketing: Problems and Solutions
Direct marketing is a process of identifying likely buyers of certain products and promoting the products accordingly. It is increasingly used by banks, insurance companies, and the retail industry. Data mining can provide an effective tool for direct marketing. During data mining, several specific problems arise. For example, the class distribution is extremely unbalanced (the response rate is about 1%), the predictive accuracy is no longer suitable for evaluating learning methods, and the number of examples can be too large. In this paper, we discuss methods of coping with these problems based on our experience on direct-marketing projects using data mining.
9181955
Answering Queries with Database Restrictions
I am a Ph.D. student in the Computer Science Department at Stanford University. My main research interests include query reformulation in the database domain. In particular, I work on the problems of how to do query planning and reformulation when relations have limited access patterns [7,9]. That is, the binding patterns of the relations require values to be specified for certain attributes in order to retrieve data from a relation. Most of my work is based on the TSIM-MIS project (http://www-db.stanford.edu/tsimmis/), a data-integration project [2,10,11] at Stanford.
9373274
A heuristic for parallel machine scheduling with agreeable due dates to minimize the number of late jobs
Abstract Given a set of identical parallel machines and a set of jobs with different due dates and release times, we consider the problem of finding a schedule such that the number of late jobs is minimized, where the given due dates and release times are assumed to be agreeable. A heuristic algorithm is presented and a dynamic programming lower bounding procedure is developed. Computational experiments are performed to show the effectiveness of the heuristic.