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Interactive concept editing in computer-human interactive learning

An interactive, machine-learning technology, applied in the field of interactive concept editing in computer-human interactive learning, can solve the problems that search engines cannot automatically understand information and reduce accuracy

Active Publication Date: 2016-03-02
MICROSOFT TECH LICENSING LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although Internet search engines generally do a reasonable job with title queries and documents, accuracy drops off rapidly at the tail end because search engines cannot automatically understand the information

Method used

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  • Interactive concept editing in computer-human interactive learning
  • Interactive concept editing in computer-human interactive learning
  • Interactive concept editing in computer-human interactive learning

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Experimental program
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Embodiment Construction

[0031] The methods described herein generate numerous engineering and scientific challenges, which are discussed below. These challenges include:

[0032] ●Active annotation exploration

[0033] ● Automatic regularization and cold start

[0034] ● Scales with number of entries and number of classifiers

[0035] ●Active characterization

[0036] ●Segmentation and summarization

[0037] In a first aspect, a computer readable medium containing computer usable instructions to facilitate a method of interactively generating a dictionary for machine learning is provided. A user interface is presented for generating a dictionary comprising a list of one or both of terms or n-grams defining concepts available as features for training the classifier. On the user interface, a positive examples field is presented, wherein the positive examples field is configured to receive user-entered terms or n-grams as positive examples of concepts, wherein the positive examples are received by ...

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PUM

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Abstract

A collection of data that is extremely large can be difficult to search and / or analyze. Relevance may be dramatically improved by automatically classifying queries and web pages in useful categories, and using these classification scores as relevance features. A thorough approach may require building a large number of classifiers, corresponding to the various types of information, activities, and products. Creation of classifiers and schematizers is provided on large data sets. Exercising the classifiers and schematizers on hundreds of millions of items may expose value that is inherent to the data by adding usable meta-data. Some aspects include active labeling exploration, automatic regularization and cold start, scaling with the number of items and the number of classifiers, active featuring, and segmentation and schematization.

Description

Background technique [0001] Very large data collections are difficult to search and / or analyze. For example, in the case of web pages, a significant portion of the data is unstructured, and the values ​​are locked within the data itself. It is not enough to store the web page of the service provider. Because this information is useful, it needs to be understood. Depending on the context, the string of numbers could be a model number, bank account number, or phone number. For example, in the context of ski products, the string "lengths: 170, 175, 180cm" refers to 3 different ski lengths, not a ski length of 1700 km. Incorrect interpretation of data can lead to useless information. [0002] For example, if a user enters the two terms "mtor" and "stock" into an Internet search engine, and the results consist primarily of web pages related to the drug mTor, the search engine fails to recognize the search as a stock quote query. As another example, if a user enters the two ter...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N99/00G06N20/00
CPCG06N20/00G06F16/951G06F40/242G06F40/30H04L1/0079H04L1/0072G06N7/01G06F3/0482
Inventor P·Y·西马德D·G·格朗吉耶L·布特欧S·A·阿默诗
Owner MICROSOFT TECH LICENSING LLC
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