Abstract: The use of data from multiple data source provides inferred air quality indices with respect to a particular pollutant for multiple areas without the addition of air quality monitor stations to those areas. Labeled air quality index data for a pollutant in a region may be obtained from one or more air quality monitor stations. Spatial features for the region may be extracted from spatially-related data for the region. The spatially-related data may include information on fixed infrastructures in the region. Likewise, temporal features for the region may be extracted from temporally-related data for the region that changes over time. A co-training based learning framework may be further applied to co-train a spatial classifier and a temporal classifier based at least on the labeled air quality index data, the spatial features for the region, and the temporal features for the region.

Abstract: A home cloud computing system employs a virtualization system to virtualize data of a device and adaptively transform type or format of the virtualized data for one or more other devices, thus leveraging resources of the device for the one or more other devices. Through data virtualization and adaptive transformation, devices of heterogeneous types are seamlessly connected to one another and can act as input or output devices for each other to create a home cloud network of devices.

Abstract: A home cloud computing system employs a virtualization system to virtualize data of a device and adaptively transform type or format of the virtualized data for one or more other devices, thus leveraging resources of the device for the one or more other devices. Through data virtualization and adaptive transformation, devices of heterogeneous types are seamlessly connected to one another and can act as input or output devices for each other to create a home cloud network of devices.

Abstract: A home cloud computing system employs a virtualization system to virtualize data of a device and adaptively transform type or format of the virtualized data for one or more other devices, thus leveraging resources of the device for the one or more other devices. Through data virtualization and adaptive transformation, devices of heterogeneous types are seamlessly connected to one another and can act as input or output devices for each other to create a home cloud network of devices.

Abstract: According to a cost-per-action advertising model, advertisers submit ads with cost-per-action bids. Ad auctions are conducted and winning ads are returned with contextually relevant search results. Each time a winning ad is selected by a user, resulting in the user being redirected to a website associated with the advertiser, a selected impression and a price is recorded for the winning ad. Periodically, an advertiser submits a report indicating a number of actions attributed to the ads that have occurred through the advertiser website. The advertiser is then charged a fee for each reported action based on the recorded prices for the winning ads and based on the number of selected impressions recorded for the winning ads.

Abstract: A classifier is built to rank documents of different languages found in a query based at least in part on similarity to other documents and the relevance of those other documents to the query. A joint ranking model, e.g., based upon a Boltzmann machine, is used to represent the content similarity among documents, and to help determine joint relevance probability for a set of documents. The relevant documents of one language are thus leveraged to improve the relevance estimation for documents of different languages. In one aspect, a hidden layer of units (neurons) represents clusters (corresponding to relevant topics) among the retrieved documents, with an output layer representing the relevant documents and their features, and edges representing a relationship between clusters and documents.

Abstract: Architecture that utilizes web search implicitly to assist users in improving writing and associated productivity. The architecture extends the authoring experience of applications of office suite applications which can draw on a web search engine to offer contextual suggestions for revision, word auto-complete, and text prediction. Web-based research and reference to users is enabled as the user writes or revises text. Suggestions are made as to how to complete a phrase or sentence using data from networks such as the Internet or intranet, to how a user how revises a word or phrase in an already-written sentence using data from the network, and to problems in writing style/writing rules. Paragraph analysis is performed to find improper language usage or errors. Prediction and revision suggestions are extracted from web search or enterprise search document summaries, and intent of the user to obtain word completion, revision assistance, and prediction suggestions is identified.

Abstract: Web server controls are provided for generating client side markups with recognition and/or audible prompting. Three approaches are disclosed for implementation of the controls.

Abstract: Web server controls are provided for generating client side markups with recognition and/or audible prompting. Three approaches are disclosed for implementation of the controls.

Abstract: Controls are provided for a web server to generate client side markups that include recognition and/or audible prompting. The controls comprise elements of a dialog such as a question, answer, confirmation, command or statement. A module forms a dialog by making use of the information carried in the controls.

Abstract: Collocation errors can be automatically proofed using local and network-based corpora, including the Web. For example, according to one illustrative method, one or more collocations from a text sample are compared with a corpus such as the content of the Web. The collocations are identified for whether they are disfavored in the corpus. Indications are provided via an output device of whether the collocations are disfavored in the corpus. Additional steps may then be taken such as searching for and providing potentially proper word collocations via a user output.

Abstract: Controls are provided for a web server to generate client side markups that include recognition and/or audible prompting. The controls comprise elements of a dialog such as a question, answer, confirmation, command or statement. A module forms a dialog by making use of the information carried in the controls.

Abstract: A content object indexing process including creating a content object knowledge index, calculating a description vector of a target content object, and indexing the target content object by searching for the description vector in the content object knowledge database. It may be difficult to search for an exact content object such as a music file or academic researcher as a conventional search index may not include related hierarchical information. A content object indexing process may add hierarchical information taken from a content object knowledge index and incorporate the hierarchical information to the index entry for a specific content object. An application of such a content object indexing process may be a world wide web search engine.

Abstract: Described is a technology in which a classifier is built to rank documents of different languages found in a query based at least in part on similarity to other documents and the relevance of those other documents to the query. A joint ranking model, e.g., based upon a Boltzmann machine, is used to represent the content similarity among documents, and to help determine joint relevance probability for a set of documents. The relevant documents of one language are thus leveraged to improve the relevance estimation for documents of different languages. In one aspect, a hidden layer of units (neurons) represents clusters (corresponding to relevant topics) among the retrieved documents, with an output layer representing the relevant documents and their features, and edges representing a relationship between clusters and documents.

Abstract: A method and apparatus determine the likelihood of a sequence of words based in part on a segment model. The segment model includes trajectory expressions formed as the product of a polynomial matrix and a generation matrix. The likelihood of the sequence of words is based in part on a segment probability derived by subtracting the trajectory expressions from a feature vector matrix that contains a sequence of feature vectors for a segment of speech. Aspects of the method and apparatus also include training the segment model using such a segment probability.

Abstract: A markup language for execution on a client device in a client/server system includes extensions for recognition.

Abstract: A sentence is accessed and at least one query is generated based on the sentence. At least one query can be compared to text within a collection of documents, for example using a web search engine. Collocation errors in the sentence can be detected and/or corrected based on the comparison of the at least one query and the text within the collection of documents.

Abstract: A server/client system for processing data includes a network having a web server with information accessible remotely. A client device includes a microphone and a rendering component such as a speaker or display. The client device is configured to obtain the information from the web server and record input data associated with fields contained in the information. The client device is adapted to send the input data to a remote location with an indication of a grammar to use for recognition. A recognition server receives the input data and the indication of the grammar. The recognition server returns data indicative of what was recognized to at least one of the client and the web server.

Abstract: A computer implemented information retrieval system is provided. The system includes a user input configured to receive a user query relative to the corpus. A machine learning classifier is trained with a first set of training data comprising anchor text relative to at least some of the documents in the corpus. A processing unit is adapted to interact with the classifier to obtain search results relative to the query using the machine learning classifier. In some aspects, the classifier is also trained with a second set of training data. A method of integrating a new document into a corpus of documents is also provided. A method of training a machine learning classifier for retrieving documents from a corpus using two distinct types of training data is also provided.

Abstract: An image advertisement system of a computing device displays as part of a display page an advertisement-infused thumbnail of an image prior to displaying the image. The image advertisement system initially receives a display page with an indication of an image to be displayed as part of the display page. The image advertisement system generates an advertisement-infused thumbnail of the image by combining advertisement content with a thumbnail of the image. The image advertisement system then displays the display page with the advertisement-infused thumbnail of the image in place of the image. The image advertisement system then replaces the displayed advertisement-infused thumbnail with the image.