Rogers Communications Inc.

Hyun Chul Lee

Liqin Xu

Darius Braziunas

Michael Cvet

Yingbo Miao

Francisco Javier Estrada Guadarrama

Kyu Lee

Byron Bondling Ma

Ke Zeng

A system and method of monitoring content stored at a plurality of locations in a location set are provided. The method comprises: determining two or more historic attributes for a first feature associated with each location; for each location in the location set, determining a first predicted attribute for the first feature associated with that location based on the historic attributes for that first feature and that location; determining a monitoring schedule in accordance with the first predicted attribute; and monitoring the content at the locations in the location set according to the monitoring schedule.

System and method for monitoring web content

Profiling systems and methods of creating and using user interest profiles are described. In some example embodiments, the method includes: creating a topic set which includes topics which are organized in a hierarchical structure which includes a plurality of topic levels including an upper topic level and a lower topic level, each topic in the lower topic level being a subtopic of at least one of the topics in the upper topic level; monitoring interest in a plurality of documents for a user to identify one or more documents-of-interest to the user; and based on the monitored interest for the user, creating an interest profile for the user by determining a measure of topical interest for the user for at least one of the topics at the upper topic level and for a subtopic of that topic, the subtopic being at the lower topic level.

Systems and methods for creating an interest profile for a user

Methods and comment association systems for associating one or more comments with one or more primary electronic documents are described. In one aspect, the method comprises: identifying, at a comment association system, one or more key terms from at least a portion of the one or more primary electronic documents; identifying, at the comment association system, one or more comments associated with the identified key terms; determining, at the comment association system, whether an identified comment is sufficiently related to the one or more primary electronic documents by calculating one or more relation score for that identified comment and comparing the relation score to one or more threshold; and if the identified comment is sufficiently related to the one or more primary electronic documents, then associating the identified comment with the one or more primary electronic documents at the comment association system.

System and method for matching comment data to text data

A method and document separation system for separating a set of related documents is described. In one aspect, the method comprises: determining, on a document selection system, quality scores for a plurality of the documents in the set of related documents; obtaining a similarity score for a plurality of pairs of documents in the set of related document; and on a document selection system, obtaining a first subset of related documents which solves an optimization problem, the first subset of related documents including a portion of the document in the set of related documents, the optimization problem being a function of one or more quality scores of the documents assigned to the first subset of related documents and one or more similarity scores of pairs of documents assigned to the first subset of related documents.

System and method for filtering documents

A phrase identification system and method are provided. The method comprises: identifying one or more phrase candidates in the electronic document; selecting one of the phrase candidates; numerically representing features of the selected phrase candidates to obtain a numeric feature representation associated with that phrase candidate; and inputting the numeric feature representation into a machine learning classifier, the machine learning classifier being configured to determine, based on each numeric feature representation, whether the phrase candidate associated with that numeric feature representation is a phrase.

System and method for phrase identification

Document cluster ranking systems and methods of ranking document clusters are described. In some example embodiments, the method comprises: obtaining, at a document cluster ranking system, a value associated with a first feature for each of a plurality of document clusters; based on the values associated with the first feature, automatically generating, at the document cluster ranking system, a plurality of first feature bins, each first feature bin defining a range of values and a bin identifier; and obtaining a score for one of the document clusters, by: i) identifying the first feature bin having a range of values which includes the obtained value associated with the first feature for that one of the document clusters; and ii) determining a score for that document cluster based on the first feature bin identifier for the identified first feature bin.

Systems and methods for ranking document clusters

A method and system for cleaning an electronic document are provided. The method comprises: identifying at least one sentence in the electronic document; numerically representing features of the sentence to obtain a numeric feature representation associated with the sentence; inputting the numeric feature representation into a machine learning classifier, the machine learning classifier being configured to determine, based on each numeric feature representation, whether the sentence associated with that numeric feature representation is a bad sentence; and removing sentences determined to be bad sentences from the electronic document to create a cleaned document.

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Thornhill, Canada

Hyun Chul Lee