Cell phones and other portable devices are equipped with a variety of technologies by which existing functionality can be improved, and new functionality can be provided. Some relate to visual search capabilities, and determining appropriate actions responsive to different image inputs. Others relate to processing of image data. Still others concern metadata generation, processing, and representation. Yet others relate to coping with fixed focus limitations of cell phone cameras, e.g., in reading digital watermark data. Still others concern user interface improvements. A great number of other features and arrangements are also detailed.

Methods and Systems for Content Processing

An intelligent automated assistant system engages with the user in an integrated, conversational manner using natural language dialog, and invokes external services when appropriate to obtain information or perform various actions. The system can be implemented using any of a number of different platforms, such as the web, email, smartphone, and the like, or any combination thereof. In one embodiment, the system is based on sets of interrelated domains and tasks, and employs additional functionally powered by external services with which the system can interact.

Intelligent Automated Assistant

....The most comprehensive guide to designing practical and efficient algorithms!.... The Algorithm Design Manual, Second Edition "...the book is an algorithm-implementation treasure trove, and putting all of these implementations in one place was no small feat. The list of implementations [and] extensive bibliography make the book an invaluable resource for everyone interested in the subject." --ACM Computing Reviews "It has all the right ingredients: rich contents, friendly, personal language, subtle humor, the right references, and a plethora of pointers to resources."-- P. Takis Metaxas, Wellesley College "This is the most approachable book on algorithms I have." -- Megan Squire, Elon University, USA This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. Expanding onthe first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students. The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Techniques, provides accessible instructionon methods for designing and analyzing computer algorithms. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography. NEW to the second edition: Doubles the tutorial material and exercises over the first edition Provides full online support for lecturers, and a completely updated and improved website component with lecture slides, audio and video Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them Includes several NEW "war stories" relating experiences from real-world applications Provides up-to-date links leading to the very best algorithm implementations available in C, C++, and Java ADDITIONAL Learning Tools: Exercises include "job interview problems" from major software companies Highlighted take-home lesson boxes emphasize essential concepts Provides comprehensive references to both survey articles and the primary literature Exercises points to relevant programming contest challenge problems Many algorithms presented with actual code (written in C) as well as pseudo-code A full set of lecture slides and additional material available at www.algorist.com Written by a well-known algorithms researcher who received the IEEE Computer Science and Engineering Teaching Award, this new edition of The Algorithm Design Manual is an essential learning tool for students needing a solid grounding in algorithms, as well as a special text/reference for professionals who need an authoritative and insightful guide. Professor Skiena is also author of the popular Springer text, Programming Challenges: The Programming Contest Training Manual.

http://www.r-5.org/files/books/computers/algo-list/common/Steven_Skiena-The_Algorithm_Design_Manual-EN.pdf

The Algorithm Design Manual

The authors develop a formal group-theoretic model, called the Cayley graph model, for designing, analyzing, and improving such networks. They show that this model is universal and demonstrate how interconnection networks can be concisely represented in this model. It is shown that this model enables the authors to design networks based on representations of finite groups. They can then analyze these networks by interpreting the group-theoretic structure graph theoretically, Using these ideas, and motivated by certain well-known combinatorial problems, they develop two classes of networks called star graphs and pancake graphs. These networks are shown to have better performance than previous networks. >

A Group Theoretic Model for Symmetric Interconnection Networks.

A group-theoretic model for symmetric interconnection networks

Personal data mining mechanisms and methods are employed to identify relevant information that otherwise would likely remain undiscovered. Users supply personal data that can be analyzed in conjunction with data associated with a plurality of other users to provide useful information that can improve business operations and/or quality of life. Personal data can be mined alone or in conjunction with third party data to identify correlations amongst the data and associated users. Applications or services can interact with such data and present it to users in a myriad of manners, for instance as notifications of opportunities.

Personal data mining

Bounds for sorting by prefix reversal

The claimed subject matter provides systems and/or methods that facilitate dynamically allocating resources (e.g., hardware, software, . . . ) supported by a third party service provider. The third party service provider can support any number of services that can be concurrently requested by several clients without user perception of degraded computing performance as compared to conventional systems/techniques due to improved connectivity and mitigated latencies. An interface component can receive a request from a client device. Further, a dynamic allocation component can apportion resources (e.g., hardware resources) supported by the third party service provider to process and respond to the request based at least in part upon subscription data. Moreover, a user state evaluator can determine a state associated with a user and/or the client device; the state can be utilized by the dynamic allocation component to tailor resource allocation.

Marketplace for cloud services resources

Hardware architecture for cloud services

A system that enables a cloud-based data repository to function as a secure ‘drop-box’ for data that corresponds to a user is provided. The ‘drop box’ can be facilitated through the use of cryptographic keying technologies. For instance, data that is ‘dropped’ by or on behalf of a particular user can be encrypted using a public key that corresponds to a user-specific private key. Thus, although the data resides within the large pool of ‘cloud-based’ data, it is protected since it can only be decrypted by using the private key, which is kept secret. The innovation can further facilitate user-centric secure storage by partitioning the cloud-based repository into multiple partitions, each of which corresponds to specific indexing criteria.

William H. Gates

Papers

Personal data mining

Bounds for sorting by prefix reversal

Marketplace for cloud services resources

Hardware architecture for cloud services

Data security in an off-premise environment