Microsoft Technology Licensing, LLC

Yahoo! Inc.

Dragomir Dimitrov Yankov

Wei Wu

Suju Rajan

Adwait Ratnaparkhi

Michael Robert Evans

Chiqun Zhang

Rajesh Girish Parekh

Scott J Gaffney

Goran Predovic

Vishwanath Tumkur Ramarao

Siddhartha Cingh Arora

Beibei Cheng

Xiaopeng Xi

Maksim Lepikhin

Simon Levi Shapiro

Vashutosh Agrawal

Aleksandar Samardzija

Nikola Todic

Alex Jordan Yuter

Stanley Ke Wei

Varun Kakkar

Tijana Bekic

Nikola Perin

Jacob Nicholas Whitbeck

Mohit Khanna

Antonios Karatzoglou

Renzhong Wang

Kupa Tsheko Muyambo Mutungu

Shekoofeh Mokhtari

Alexander Rusnak

Senthil Kumar Palanisamy

Wanlin Pang

Dun Liu

Pavel Berkhin

A technique automatically identifies and resolves prohibited maneuvers in candidate routes generated by a routing system. Examples of prohibited maneuvers include traveling over a non-navigable path, traveling in an incorrect direction over a roadway, and an improper turn. The technique determines whether the candidate routes contain prohibited maneuvers by comparing the candidate routes with plural types of route-related validation data in plural respective validation processes. For example, a first validation process compares the candidate routes with a collection of GPS traces. A second validation process compares the candidate routes with map reference data. The technique further includes provisions for correcting the causes of identified prohibited maneuvers. Overall, the technique reduces the amount of manual effort involved in verifying the accuracy of routes produced by the routing system, and improves the accuracy, reliability, and safety of the routing system.

Identifying and resolving prohibited maneuvers in routes generated by a routing system

The present disclosure relates to systems, devices, and methods for suggesting geographic results to a user. The systems, devices, and methods may include receiving a prefix for a geographic query and ranking received candidate results for the prefix of the geographic query. The systems, devices, and methods may provide a query expansion based on a highest ranked candidate result. The systems, devices, and methods may determine a likelihood of the user selecting the query expansion, and if the likelihood exceeds a threshold, provide the query expansion.

Maps auto-complete through query expansion

Described herein are technologies related to generating a predicted routine of a user of a mobile computing device. Location entries generated by the mobile computing device are processed to generate visit entries, wherein the visit entries are representative of visits made by the user to places over several days. An input sequence of states is constructed based upon the visit entries, wherein each state has a place identifier assigned thereto, and further wherein each state corresponds to a time interval of predefined length. A predicted routine of the user is generated based upon the input sequence of states.

Computing system that generates a predicted routine of a user

Described herein are technologies relating to assigning wireless beacons to positions within a building, wherein the wireless beacons are included in an indoor positioning system. A computer-implemented floorplan representation is generated, wherein the representation includes a layout of the building and materials of structures of the building. Coverages of wireless beacons are simulated, and multiple objectives are balanced to identify a number of wireless beacons to deploy in the building and positions in the building where the wireless beacons are to be deployed.

Computing system that is configured to assign wireless beacons to positions within a building

Technology is described herein for ranking candidate result items in at least two stages. In a first stage, the technology uses a first attention-based neural network to determine an extent of attention that each token of an input query should pay to the tokens of each candidate result item. In a second stage, the technology uses a ranking subsystem to perform listwise inference on output results provided by the first stage, to generate a plurality of ranking scores that establish an order of relevance of the candidate results items. The ranking subsystem may use a second attention-based neural network to perform the listwise inference. According to some implementations, the technology is configured to process queries and candidate result items having different kinds and combinations of features. For instance, one kind of input query may include text-based features, structure-based features, and geographic-based features.

Processing queries using an attention-based ranking system

The present disclosure is directed to systems, methods and devices for replacing a static map image with an interactive map that approximates the geographic area depicted by the static map image. A static image may be inspected and a determination may be made as to whether the static image meets a map identification threshold value. At least one signal associated with the static image may be evaluated and based on that evaluation at least one geo-entity of intent may be identified. The static image may be replaced with a static image corresponding to at least one of the identified geo-entities of intent.

Conversion of static images into interactive maps

Methods, systems, and computer programs for categorizing the sensitivity of web pages are presented. In one method, a space of sensitive pages is identified based on the sensitivity categorization of a first plurality of web pages and a second plurality of web pages. The first plurality of web pages is obtained by performing search queries using known sensitive words, and the second plurality of web pages includes randomly selected web pages. Additionally, the method identifies a third plurality of web pages that includes web pages on or near the boundary between the space of sensitive pages and the space of non-sensitive pages. The space of sensitive pages is then redefined based on the sensitivity categorization of the first, second, and third pluralities of web pages. Once the space of sensitive pages is defined, the method is used to determine that a given web page is sensitive when the given web page is in the space of sensitive pages. Web pages are included in a marketing operation when the web pages are not sensitive.

Sensitivity categorization of web pages

A system for training classifiers in multiple categories through an active learning system, including a computer having a memory and a processor, the processor programmed to: train an initial set of m binary one-versus-all classifiers, one for each category in a taxonomy, on a labeled dataset of examples stored in a database coupled with the computer; uniformly sample up to a predetermined large number of examples from a second, larger dataset of unlabeled examples stored in a database coupled with the computer; order the sampled unlabeled examples in order of informativeness for each classifier; determine a minimum subset of the unlabeled examples that are most informative for a maximum number of the classifiers to form an active set for learning; and use editorially-labeled versions of the examples of the active set to re-train the classifiers, thereby improving the accuracy of at least some of the classifiers.

System for training classifiers in multiple categories through active learning

Multiple features of email traffic are analyzed and extracted. Feature vectors comprising the multiple features are created and cluster analysis is utilized to track spam generation even from dynamically changing or aliased IP addresses.

Classification and cluster analysis spam detection and reduction

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Sunnyvale, CA, United States of America

Dragomir Dimitrov Yankov