Microsoft Technology Licensing, LLC

Xiaojiang Liu

Ji-Rong Wen

Zaiqing Nie

Jun Zhu

Bo Zhang

Ying-Qing Xu

Gang Luo

Yong Cao

Ruochi Zhang

Yunxiao Ma

The automated social networking graph mining and visualization technique described herein mines social connections and allows creation of a social networking graph from general (not necessarily social-application specific) Web pages. The technique uses the distances between a person's/entity's name and related people's/entities names on one or more Web pages to determine connections between people/entities and the strengths of the connections. In one embodiment, the technique lays out these connections, and then clusters them, in a 2-D layout of a social networking graph that represents the Web connection strengths among the related people's or entities' names, by using a force-directed model.

Automated networking graph mining and visualization

Automated social networking graph mining and visualization

Methods and systems for Web-scale entity relationship extraction are usable to build large-scale entity relationship graphs from any data corpora stored on a computer-readable medium or accessible through a network. Such entity relationship graphs may be used to navigate previously undiscoverable relationships among entities within data corpora. Additionally, the entity relationship extraction may be configured to utilize discriminative models to jointly model correlated data found within the selected corpora.

Displaying search results with edges/entity relationships in regions/quadrants on a display device

Techniques for displaying a relationship graph are described herein. In one example, a search term may be used to obtain a plurality of documents from a network, such as the Internet. A plurality of entities, and relationships between at least some of those entities, may be extracted from the documents. In an example user interface, representations of a plurality of entities may be displayed, such as by shapes (e.g., circles) labeled to identify people or organizations. Edges (e.g., lines) may be used to connect different representations of entities and to thereby indicate a relationship between the connected entities. In a particular example, input from movement of a cursor over an edge may result in display of a description of a relationship between the connected entities. In a further particular example, size of each entity may be related to a number of connections each has with others.

Web-scale entity relationship extraction

Web-scale entity relationship extraction that extracts pattern(s) based on an extracted tuple

Growing community of inventors

Beijing, China

Xiaojiang Liu