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Marcus Fontoura

Researcher at Microsoft

Publications -  125
Citations -  4048

Marcus Fontoura is an academic researcher from Microsoft. The author has contributed to research in topics: Set (abstract data type) & Inverted index. The author has an hindex of 33, co-authored 122 publications receiving 3606 citations. Previous affiliations of Marcus Fontoura include Princeton University & Google.

Papers
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Patent

System and Method to Facilitate Classification and Storage of Events in a Network

TL;DR: In this article, a system and method to facilitate classification and storage of events in a network is described, where an event and associated content information are received from an entity over a network.
Patent

Query classification and selection of associated advertising information

TL;DR: In this article, a system and method to facilitate classification of search queries and selection of associated advertising information over a network is described, where a search query is processed to retrieve a predetermined number of query results and then classified to select one or more categories associated with the query results.
Journal ArticleDOI

Using refactoring and unification rules to assist framework evolution

TL;DR: The use of refactoring and unification rules to assist framework evolution is proposed and illustrated through the JUnit testing framework.
Patent

Method, system and article of manufacture for searching documents for ranges of numeric values

TL;DR: In this paper, a system and article of manufacture for searching documents for ranges of numeric values is presented. But the system is limited to a single document and requires that each document identifier is associated with at least one value in the set of values included in the document identified by the document identifier.
Patent

System and Method to Facilitate Mapping and Storage of Data Within One or More Data Taxonomies

TL;DR: In this article, a system and method to facilitate mapping and storage of data within one or more data taxonomies is described, where content information is received over a network and analyzed to determine at least one theme representing subject matter related to the content information.