Microsoft Technology Licensing, LLC

Oscar Gerardo Naim

Lucretia Henrica Vanderwende

Krist Wongsuphasawat

George G Robertson

Chris Demetrios Karkanias

Jonathan Edgar Fay

Brian Scott Aust

Praveen Seshadri

Donald Frank Brinkman, Jr

Ciprian Gerea

James Kelsey Howey

Michiel Johannes Wories

Yin Xie

Hongfei Guo

James A Holt

Sethu Srinivasan

Daniel T Jones

Grigory Pogulsky

Puneet Hariharan

Maciek Sarnowicz

Vipul M Shah

Sonia Patricia Carlson

Michael Jonathan Galos

A mixed-initiative annotation framework is described herein. A document that includes several sentences is presented to a user, and an extractor module analyzes at least one sentence and automatically extracts a subject, predicate, object triple therefrom. The subject, predicate, object triple is displayed in graphical relation with the sentence as a proposed annotation to the sentence. Graphical options are presented to the user that allow the user to accept the proposed annotation, reject the proposed annotation, or modify the proposed annotation.

Validation, rejection, and modification of automatically generated document annotations

A graphical user interface that facilitates annotating documents is described herein. The graphical user interface includes a first field that displays a document to a user. The graphical user interface includes a second field that displays an annotation that has been assigned to a portion of the document, wherein the annotation includes a defined structure. The annotation is in the form of a tuple, wherein the tuple includes a first word or phrase, a second word or phrase, and a third word or phrase that relates the first word or phrase to the second word or phrase. The graphical user interface also includes a third field that facilitates user-editing of annotations.

Graphical user interface that supports document annotation

Technologies pertaining to annotation aggregation are described herein. A user of a computing device assigns an annotation to a portion of a document, wherein the annotation comprises a tuple. The tuple comprises semantic relationships amongst words or phrases in the document. Relationship data is also generated, wherein the relationship data identifies the document, the author of the document, the author of the annotation, and other data. The annotations and relationship data are transmitted to a data store, where such information is aggregated with other annotations made by other annotators to various documents, thereby creating a network of knowledge

Aggregating document annotations

Generation of a graphical visualization that summarizes a research document is described herein. A data store includes first data that identifies a first research document, second data that identifies a second research document that includes a citation to the first research document, and at least a portion of a sentence in the second research document that includes the citation to the first research document. A graphical visualization is generated that includes a first node that is representative of the first research document, a graphical object that indicates that the second research document includes the citation to the first research document, and the at least the portion of the sentence that includes the citation.

Generating visual summaries of research documents

Described herein are technologies pertaining to generating co-citation graphs. A context-informative co-citation graph includes a first node that represents a first research document, a second node that represents a second research document, and a third node that represents a third research document that includes a citation to both the first research document and the second research document. The context-informative co-citation graph also includes a first edge that couples the first node and the third node, and a second edge that couples the second node and the third node. The two edges visually indicate that the first research document and the second research document are co-cited by the third research document. The context-informative co-citation graph further includes at least a portion of a sentence in the third research document that includes a citation to at least one of the first research document or the second research document.

Generation of context-informative co-citation graphs

Described herein are technologies that facilitate representing instances in time over 62 orders of magnitude as well as graphically depicting events over various time ranges and resolutions in time. A filter window is selected as a function of a resolution of a display, such filter window is applied over a representation of an instant in time. The position of the filter window along the representation of the instant in time defines a resolution in time, and such resolution in time is utilized to select graphical objects for display.

Display of temporal data over multiple orders of magnitude

Described is a technology for composing queries by user interaction with objects and facets. A facet-based user interface allows users to select facets for use as filtering criteria, and a logic-based user interface allows users to logically combine object data. Query logic that processes the filtering criteria and/or logically combines the object data into a query. The facet-based user interface and logic-based user interface may be accessed via a unified user interface. The unified user interface may also provide a text editor for composing a text-based query.

Facet, logic and textual-based query composer

Automated sampling and aggregation of performance or other dynamically varying data facilitates user productivity by making data available for a wide range of uses. An automated sampling and aggregration system includes one or more types of data collectors, including a dedicated data collector per machine, multiple data collectors per machine, or an instance-less data collector.

Extensible data collectors

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Redmond, WA, United States of America

Oscar Gerardo Naim