Microsoft Technology Licensing, LLC

Jiang-Ming Yang

Lei Zhang

Rui Cai

Wei-Ying Ma

Wei Wang

Haifeng Li

Changhu Wang

Yan Ke

Xin-Jing Wang

Xiaodong Fan

Xiaosong Yang

Xiao Kong

Xin Lu

Shouqiu Yu

Systems, methods, and devices are described for providing customized trip plans. Based on information provided by a user, geo-tagged photographs, and/or travelogues, one or more travel destinations are identified. Travel paths typically taken by tourists within each of the travel destinations and stay times within those travel destinations may be determined. A customized trip plan including a travel route plan among the one or more travel destinations and recommended internal paths within each travel destination are provided to the user. A revised customized trip plan may also be provided in response to changes made to information associated with the user.

Travel route planning using geo-tagged photographs

A classifier may be integrated into a pipeline of a general web crawler. The classifier may classify crawled webpages as either video pages or non-video pages. Video pages and information regarding domain importance may be aggregated. Ones of the domains of the video pages may be selected based on domain importance rankings. Webpages of the selected domains may be randomly sampled. The sampled webpages may be structurally analyzed and hint information may be generated with respect to each of the selected domains. The hint information may guide a deep crawling operation for discovering all video pages within the selected domains. Video links within the video pages may be found, one or more videos may be downloaded, and one or more representations of the one or more videos may be indexed.

Automatic online video discovery and indexing

A pattern tree is constructed based on a plurality of key-value pairs representing portions of a data set. In some implementations, the pattern tree may be used for learning one or more rules for interacting with a source of the data set.

Pattern tree-based rule learning

Website design pattern modeling technique embodiments are presented that model a website's design patterns. This can be based on the website's layout elements, its URL tokens, or both. When based on both, the design patterns can be modeled separately using first the layout elements and then the URL tokens, or vice versa. Alternately, the modeling can be based on coupled layout and URL token patterns. In operation, the modeling involves first identifying layout elements and/or URL tokens found on at least some of the pages of the website. The website design patterns are then modeled based on the occurrences of the identified layout elements and/or URL tokens in pages of the website. In cases where a coupled modeling scheme is employed, a modeling technique that exploits the correlations between the layout elements and URL tokens is used.

Website design pattern modeling

A simultaneous semantic and structure threaded discussion modeling system and method for generating a model of a discussion thread and using the model to mine data from the discussion thread. Embodiments of the system and method generate a model that contains both semantic terms and structure terms. The model simultaneously models both semantics and structure of the discussion thread. A model generator includes a semantic module generates two semantic terms for the model and a structure module generates two structure terms for the model. The generator combines the two semantic terms and the two structure terms to generate the simultaneous semantic and structure model. Embodiments of the system and method include an applications module, which contains three application that use the model to reconstruct reply relations among posts in the discussion thread, identify junk posts in the discussion thread, and find experts in each sub-board of web forums.

Modeling semantic and structure of threaded discussions

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Beijing, China

Jiang-Ming Yang