A service to enable interactive search experiences within structured data via natural language inputs.
In the field of computer science, large-scale experimentation on users is not new: there have been many efforts in both the public and private sectors to analyze users and to create experimental conditions to provoke changes in their behavior. However, new autonomous and semi-autonomous systems for experimentation, driven by techniques from AI and machine learning, raise important questions for the field. Many of these questions are about the social and ethical implications of these systems.
Labs: New York
The capability of managing personal photos is becoming crucial. In this work, we have attempted to solve the following pain points for mobile users: 1) intelligent photo tagging, best photo selection, event segmentation and album naming, 2) speech recognition and user intent parsing of time, location, people attributes and objects, 3) search by arbitrary queries.
The Dual Embedding Space Model (DESM) is an information retrieval model that uses two word embeddings, one for query words and one for document words. It takes into account the vector similarity between each query word vector and all document word vectors.
Mobius (formerly known as Spark-CLR) is an cross-company open source project to provide C# language bindings for Apache Spark, which is a cluster computing framework built around the core programming abstractions of Resilient Distributed Datasets (RDDs), a logical collection of data partitioned across machines, and Discretized Streams (DStreams), a temporal sequence of RDDs.
The Distributed Social Analytics Platform (DSoAP) project is focused on the “Huge Data” problem in social policy research caused by the breadth of data involved. Using aggregate social media data to investigate and validate social issues such as employment, health and fiscal policy requires analyzing many months or years of data. DSoAP is applying intelligent compaction, pre-indexing and distribution of data across a server cluster to achieve responsive query times for online data exploration.
Keep current on key events, people, papers, and conferences.
Building a computer system to automatically solve math word problems written in natural language.
The Microsoft Academic Graph is a heterogeneous graph containing scientific publication records, citation relationships between those publications, as well as authors, institutions, journals and conference "venues" and fields of study. This data is available as a set of zipped text files stored in Microsoft Azure blob storage and available via HTTP.
Project Catapult is a Microsoft venture that investigates the use of field-programmable gate arrays (FPGAs) to improve performance, reduce power, and provide new capabilities in the datacenter.
Deep Structured Semantic Model / Deep Semantic Similarity Model
Given a concept name, and seed entities, return entities and tables in this concept.
Website for the CIKM2014 tutorial on Deep Learning for Natural Language Processing: Theory and Practice (more content to be added)
Using the Internet as an (noisy) knowledgebase to mine semantics for multimedia data.
We built the Sketch2Cartoon system, which is an automatic cartoon making system. It enables users to sketch major curves of characters and props in their mind, and real-time search results from millions of clipart images could be selected to compose the cartoon images. The selected com- ponents are vectorized and thus could be further edited. By enabling sketch-based input, even a child who is too young to read or write can draw whatever he/she imagines and get interesting cartoon images.
We built the Sketch2Tag system for hand-drawn sketch recognition. Due to large variations presented in hand-drawn sketches, most of existing work was limited to a particular domain or limited pre-defined classes. Different from existing work, Sketch2Tag is a general sketch recognition system, towards recognizing any semantically meaningful object that a child can recognize. This system enables a user to draw a sketch on the query panel, and then provides real-time recognition results.
Microsoft Research is happy to continue hosting this series of Image Recognition (Retrieval) Grand Challenges. Do you have what it takes to build the best image recognition system? Enter these MSR Image Recognition Challenges in ACM Multimedia and/or IEEE ICME to develop your image recognition system based on real world large scale data.
We argue that the massive amount of click data from commercial search engines provides a data set that is unique in the bridging of the semantic and intent gap. Search engines generate millions of click data (a.k.a. image-query pairs), which provide almost "unlimited" yet strong connections between semantics and images, as well as connections between users' intents and queries. This site is to introduce such as dataset, Clickture.
Mobile video is quickly becoming a mass consumer phenomenon. More and more people are using their smartphones to search and browse video contents while on the move. This project is to develop an innovative instant mobile video search system through which users can discover videos by simply pointing their phones at a screen to capture a very few seconds of what they are watching.
Stroke Recovery with Kinect is an interactive rehabilitation system that helps stroke patients improve their upper-limb motor functioning in the comfort of their own home. By using the Microsoft Kinect sensor’s gesture recognition technology, the system recognizes and interprets the user’s movements, assesses their rehabilitation progress, and adjusts the level of difficulty for subsequent therapy sessions.
MSRA Mood Board
Exploratory queries on a database often returns too few or too many results (e.g., a home search query on a database of available homes). In such cases, the user faces the challenges of (i) navigating through too many results and/or (ii) refining the query. This project focuses on innovative ways to help the user when the face the above challenges.
The same entity is often referred to in a variety of ways. For example, the camera Canon 600d is also referred to as "canon rebel t3i", the celebrity Jennifer Lopez is also referred to as "jlo" and Seattle Tacoma International Airport is also referred to as "sea tac". These are known as synonyms. Without knowledge of synonyms, many applications like e-commerce search will fail to return relevant results. We leverage the data assets amassed by Bing to automatically mine such synonyms.
We are working toward a theoretical foundation of developing large-scale human-machine systems that combine the intelligence of human and the computing power of machine to solve the problems that are difficult to solve by either human or machine alone.
AutoTag 'n Search My Photos, a Microsoft Garage project, uses photos tagged in your Facebook account to learn face models of your friends. It can then automatically tag faces in your personal photo collection in Pictures Library, including OneDrive Camera roll. The app supports the ability to search for people tags across your photo collection. AutoTag ‘n Search My Photos adds new people tags to your photos and does not overwrite any existing tags.