Microsoft Technology Licensing, LLC

Rosetta Inpharmatics, Inc.

Steven J Altschuler

Lani Fang Wu

Greg Ridgeway

David V Ingerman

Edward K Y Jung

Alejandro Acero

Daniel D Shoemaker

Lei Zhao

Christopher D Armour

William E Kim

Stewart Scherer

Sound source separation, without permutation, using convolutional mixing independent component analysis based on a priori knowledge of the target sound source is disclosed. The target sound source can be a human speaker. The reconstruction filters used in the sound source separation take into account the a priori knowledge of the target sound source, such as an estimate the spectra of the target sound source. The filters may be generally constructed based on a speech recognition system. Matching the words of the dictionary of the speech recognition system to a reconstructed signal indicates whether proper separation has occurred. More specifically, the filters may be constructed based on a vector quantization codebook of vectors representing typical sound source patterns. Matching the vectors of the codebook to a reconstructed signal indicates whether proper separation has occurred. The vectors may be linear prediction vectors, among others.

Sound source separation using convolutional mixing and a priori sound source knowledge

Methods and apparatus for analyzing tasks performed by computer users by (i) gathering usage data, (ii) converting logged usage data into a uniform format, (iii) determining or defining task boundaries, and (iv) determining a task analysis model by &ldquo;clustering&rdquo; similar tasks together. The task analysis model may be used to (i) help users complete a task (such help, for example, may be in the form of a gratuitous help function), and/or (ii) to target marketing information to users based on user inputs and the task analysis model. The present invention also provides a uniform semantic network for representing different types of objects in a uniform way.

Methods and apparatus for analyzing computer-based tasks to build task models

The invention relates to methods and systems (e.g., computer systems and computer program products) for identifying and characterizing genes using microarrays. In particular, the invention provides for improved, robust methods for detecting genes through the use of microarrays to analyze the expression state of the genome. Genes which are expressed can be mapped to their respective positions in the genome, and the structure of such genes can be determined.

Gene discovery using microarrays

Methods and apparatus for using task models to help computer users complete tasks

A pattern lattice data space as a framework for analyzing data, in which both schema-based and statistical analysis are accommodated, is defined. Ways to manage the size of the lattice structures in the pattern lattice data space are described. Utilities to classify or cluster, search (find similar data), or relate data using lattice fragments in the pattern lattice data space are also described. Superpattern cone or lattice generation function, which may be used by the classification and clustering functions, is also described. In addition, a subpattern cone or lattice generation process, which may be used by the search (find similar data) and data relating functions, is also described. Finally, a function to label, in readily understandable &ldquo;pidgin&rdquo;, categories which classify information, is also described.

Methods and apparatus for finding semantic information, such as usage logs, similar to a query using a pattern lattice data space

Methods and apparatus using task models for targeting marketing information to computer users based on a task being performed

Entering and evaluating group(s) of similar dependence hypotheses, such as time dependence hypotheses, and forecasting values of a variable based on the group(s) of similar dependence hypotheses. The group(s) of similar dependence hypotheses may be used to forecast requests for an Internet resource or Internet resources having one or more particular attributes. The entered group(s) of similar dependence hypotheses may be evaluated based on known data, such as past requests for Internet resources or Internet resources of a particular type.

Methods and apparatus for entering and evaluating time dependence hypotheses and for forecasting based on the time dependence hypotheses entered

Building resource (e.g., Internet content) and attribute transition probability models and using such models for pre-fetching resources, editing resource link topology, building resource link topology templates, and collaborative filtering.

Methods and apparatus for building attribute transition probability models for use in pre-fetching resources

Methods and apparatus for using attribute transition probability models

Resource usage data is used to infer degrees of influence between users. Once such inferences are made, a directed graph representation of the users and the inferred 'influence' between the users can be generated. 'Influential rumormongers' can then be determined from the directed graph, for example, by using a greedy graph covering algorithm. In this way, marketing information can be targeted to 'influential rumormongers' to optimize its dissemination and impact. If actual (explicit) data regarding the influence between users is known, such data may be used to refine or replace at least some edge values.

Methods and apparatus for determining or inferring influential

Methods and apparatus for using resource transition probability models

Methods and apparatus for building resource transition probability

A method, system and computer product for allowing efficient user interaction with digital time-based signals. User control and filter information (symbolic, procedural or a combination of both) are optimized for greatly improving calculating efficiency. First, filters are symbolically optimized. Then, a single optimized procedure is generated and compiled into an optimized procedure code. The procedure code then processes the input signal according to control information.

Growing community of inventors

Redmond, WA, United States of America

Steven J Altschuler