Lexisnexis, a Division of Reed Elsevier Inc.

Relx Inc.

Lexisnexis Group

Mark Wasson

Harry R Silver

Paul Zhang

Sanjay Sharma

David Steiner

Valentina Templar

Donald Loritz

James S Wiltshire, Jr

Andrew L Freisthler

Shian-jung Chen

Ling Qin Zhang

Steve Xu

Martin R Kilmer

Eleni Koutsomitopoulou

E Scott Wetzel

Shian-Jung Chen

James Wiltshire

Systems and methods for generating issue networks are disclosed. In one embodiment, a computer-implemented method of generating an issue network from a document corpus includes searching, using a computer, the document corpus for a set of documents discussing a starting issue, wherein the starting issue is one of a plurality of normalized issues defined by the document corpus. The method further includes determining a set of normalized issues discussed by the set of documents discussing the starting issue, wherein the set of normalized issues also includes the starting issue, and determining instances of co-occurrences of individual normalized issues of the set of normalized issues within individual cases of the set of documents. The method also includes linking individual normalized issues of the set of normalized issues based on their co-occurrences within the set of documents, wherein the linked individual normalized issues at least in part define the issue network.

Systems and methods for generating issue networks

Disclosed herein are systems and methods for linking items into common matters. Some embodiments of the systems and/or methods may retrieve an electronic document from a source, determine whether the electronic document is associated with a predetermined first matter, and in response to determining that the electronic document is associated with the predetermined first matter, link the electronic document to the predetermined first matter. Similarly, in some embodiments, the systems and methods may further create a second matter and may link the electronic document to the second matter, such that accessing the electronic document can provide other documents linked to the second matter, receive a request for the electronic document, and in response to receiving the request for the electronic document, provide a user option to provide access to the other documents linked to the predetermined first matter.

Systems and methods for linking items to a matter

Methods and systems are provided for normalizing strings and for matching records. In one implementation, a string is tokenized into components. Sequences of tags are generated by assigning tags to the components. A sequence of states is determined based on the sequences of tags. A normalized string is generated by normalizing the sequence of the states. A key record including key fields is extracted from a first data source. A candidate record including candidate fields is extracted from a second data source. A numerical record including numerical fields is computed by comparing the key fields and the candidate fields using comparison functions. Matching functions determined by an additive logistic regression method are applied to the numerical fields. Whether the key record and the candidate record are a match is determined based on a sum of results of the matching functions.

Methods and systems for matching records and normalizing names

A fact extraction tool set ('FEX') finds and extracts targeted pieces of information from text using linguistic and pattern matching technologies, and in particular, text annotation and fact extraction. Text annotation tools break a text, such as a document, into its base tokens and annotate those tokens or patterns of tokens with orthographic, syntactic, semantic, pragmatic and other attributes. A user-defined 'Annotation Configuration' controls which annotation tools are used in a given application. XML is used as the basis for representing the annotated text. A tag uncrossing tool resolves conflicting (crossed) annotation boundaries in an annotated text to produce well-formed XML from the results of the individual annotators. The fact extraction tool is a pattern matching language which is used to write scripts that find and match patterns of attributes that correspond to targeted pieces of information in the text, and extract that information.

System and method for extracting information from text using text annotation and fact extraction

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Seattle, WA, United States of America

Mark Wasson