E-Discovery Tip Sheet
|
|
- Jasper Price
- 8 years ago
- Views:
Transcription
1 E-Discovery Tip Sheet LegalTech 2015 Some Panels and Briefings Last month I took you on a select tour of the vendor exhibits and products from LegalTech This month I want to provide a small brief that might provide a little more incentive to brave the cold and crowds next time around. Below I have digested one plenary session, and two vendor briefings from kcura on developments in their industry-leading review platform, Relativity 9. A. Legal Tech Panel Session: Taking TAR to the Next Level: Recent Research and the Promise of Continuous Active Learning This panel was comprised of Professor Gordon Cormack of University of Waterloo and Maura R. Grossman of Wachtell Lipton, co-authors of a cornerstone study of technology assisted review; Magistrate Judge Andrew Peck, a leading voice from the Federal bench on ediscovery issues; Susan Nielsen Hammond, General Counsel of Regions Financial Corporation; and moderator John Tredennick of big data review vendor Catalyst Systems. To boil down a deep and interesting discussion, the evolution and efficacy of several classes of computer assisted review were compared to the false gold standard (per Judge Peck) of linear manual review, and to each other. Ms. Grossman, followed up by Professor Cormack, used slides to illustrate the differences in process and efficacy of three different types of computer learning: > Simple Passive Learning (SPL): 1. Critical initial factors are (a) seed set selection random vs. judgmental; and (b) number of documents in the seed set.
2 March 2015 E-Discovery Tip Sheet Page 2 2. Review and code seed set (by Expert, i.e., senior attorney on case). 3. Feed expertly-coded seed set to algorithm; evaluate machine vote effectiveness and training result. 4. Repeat as required to stabilize results ( till the Popcorn stops popping, or the stability does not materially change). 5. When done, run results against entire document set. 6. Review documents auto-coded Responsive or above confidence ranking percentile cut-off. 7. Team chooses next set to review. > Simple Active Learning (SAL): 1. Create Control Set think of as a Responsive key for benchmark. 2. Critical factors in seed set selection are random vs. judgmental, and number of documents in set, as above. 3. Review and code seed set (by Expert ). 4. Use machine learning algorithm to select documents from which it will learn the most (ambiguous content). 5. Still an iterative process until stable (all the popcorn is popped). > Continuous Active Learning (CAL): 1. Seed set (initial training set) selection is judgmental; also dependent on number of documents in set. Inferentially, some initial document counts have been calculated that seem to create a stable set under multiple circumstances (between about 5,000 and 14,000). Example given was to put in one or more party s Request for Production as part of the set. 2. Machine learning algorithm based upon review. (a) Review and code newly suggested documents and add to training set.
3 March 2015 E-Discovery Tip Sheet Page 3 (b) Repeat until substantially all documents have been reviewed. 3. Iterative, constant review and feedback. Professor Cormack noted, in reviewing the higher recall of CAL, that search term-based seed sets contain a built-in STOP, limited by the keyword hits, even within TAR. Analyses were offered of recall versus effort in a first-level doc review: for example, 56,000 documents were required in SPL to reach the same level of recall as 5,000 documents in SAL. Ms. Hammond added a practical perspective on the theoretical and judicial discussions: in regulatory practice, precision is vital. Having used most of the types of tools under discussion, she noted that testing is needed for determining good seed sets, and continues to be required as new terms arise during review. She recommended a blended approach continuing to engage human intelligence. A toolkit and resources for the Cormack & Gordon SIGIR 14 report, including 4 Text Retrieval Conference (TREC) 09 Enron databases which were part of those used for the controlled comparison of SPL, SAL and CAL cited, are available for free under the GPL at trec.nist.gov, among other sources. B. kcura Relativity Briefings 1. The Mobile Attorney: Working with Key Documents Using Relativity Binders. Relativity v8 and later can export and synchronize Binder data with an ipad in this Mobile and Web application that helps consolidate critical case documents. Binders are locked behind the Apple encryption keychain for security. Relativity field settings control metadata, docket or coding output, with contents based upon a Saved Search. Binder users must already be licensed Relativity users. Among the limited palette of features available to mobile Binder users are: - Annotations (highlight, note, draw, control colors and thickness only see own); - Organization (create Sections, drag and drop); - Search of metadata or text (builds an index on the ipad, with highlights on hits; must use UPPERCASE only for Boolean AND, OR, NOT);
4 March 2015 E-Discovery Tip Sheet Page 4 - Offline Access (sync with Relativity as Backup, visible only to individual Binders user, via HTTPS or SSL); - AirPlay ipad Binder info can be wirelessly projected to Apple TV; and - Binders on Web (Binder viewer, track changes, sync across multiple devices). One can do incremental Binder builds, with updates and additions; won t remove anything, though. Apple ios will warn on space, and can set auto-expire to clear. With Relativity 9, users will be able to publish to Binders, even push a single doc to a pre-made Binder. There will also be mobile device management and security configuration, as well as added Notifications, Favorites, Preview before download (but no filesize parameter); the beta is due in March/April Must have Native Imaging Server (the processing bit add-on module, which requires additional servers) to use Binders. This is NOT a collaborative tool at this point. 2. Relativity Analytics Overview. The presenter discussed analytics in case workflow as ideal where there is a short time line, such as in a Federal second request on a prospective merger, and a lot of data to get through. She cited that the average case here was about 1M docs, and the top 1000 cases were about 3.8M docs. Relativity Analytics is thus intended to (a) investigate an unknown data set for doc types, languages, and find related documents; (b) evaluate large sets of data and prioritize; or (c) structure documents by batching out clusters. The presenter broke it out as follows: > Threading (based on Content Analyst) identify a group within a conversation; display groupings; show master inclusive (indicated by a solid dot). > Near Duplication organization of highly similar text into relational groups with percentage of similarity; used for review batching or conflict check, or to find subtle differences in language between documents. > Language Identification Determine primary and up to 2 secondary languages per document; report percentage of text in each language found; handles 172 languages and
5 March 2015 E-Discovery Tip Sheet Page 5 dialects. Used to assign documents to language review teams, create grand total charts and reports, and further classification. One cannot exclude text, at least in Relativity 8. The above fall into the category of Document Organization and Structure. Next are Conceptual Analytics: > Latent Semantic Analysis mathematical assessment of language learned from documents in the current case, based upon concepts, not words - aboutness (about a plan, RFP re subject, precis of blog post content), versus more common - is-ness (metadata, keyword, proximity, document type, author). > Search using example sentence, paragraph, entire document to return documents related in concept, based on ideas and thus conceptual relevancy to get around false keyword hits, misspellings and code words. > Keyword expansion submit a term to list conceptually-related items - Develop a search term list (synonyms). - Learn language of a case (jargon/ new terms / idiom). - Revealing code words and variations. Last are the Review and QC analytics: > Clustering group documents by concept and visual hierarchy (a title is provided for each cluster of 4 words found together). One can then batch out by cluster (# of docs, score e.g. 0.65). The process runs an index of all documents in the workspace, or by custodian, or by set submitted for Analytics clustering. This facilitates Mass actions, e.g., Mass Tag a certain cluster Not Relevant. One can batch out either using or overriding the Family Field Group identifier. > Categorization Based upon expert user-defined examples or categories, using example documents from Relativity Assisted Review. Use for Prioritization, sorting large volumes quickly, or creating a pivot table to visualize clusters against categories. Under the Indexing & Analytics Tab, can set example source (e.g., Tag), maximum
6 March 2015 E-Discovery Tip Sheet Page 6 categories per document, minimum coherent score (default = 70%) and issue designation. The above notes represent a tiny fraction of what was on offer at LegalTech. The show truly is one place and time where legal technology people, knowledge and commerce converge. Hope to see you there next year! -- Andy Kass akass@uslegalsupport.com The views expressed in this E-Discovery Tip Sheet are solely the views of the author, and do not necessarily represent the opinion of U.S. Legal Support, Inc. U.S. LEGAL SUPPORT, INC. ESI & Litigation Services PROVIDING EXPERT SOLUTIONS FROM DISCOVERY TO VERDICT e-discovery Document Collection & Review Litigation Management Litigation Software Training Meet & Confer Advice Court Reporting Services At Trial Electronic Evidence Presentation Trial Consulting Demonstrative Graphics Courtroom & War Room Equipment Deposition & Case Management Services Record Retrieval Copyright 2015 U.S. Legal Support, Inc., 425 Park Avenue, New York NY (800) All rights reserved. To update your address or unsubscribe from these mailings, please reply to this with CANCEL in the subject line.
E-Discovery Tip Sheet
E-Discovery Tip Sheet A TAR Too Far Here s the buzzword feed for the day: Technology-assisted review (TAR) Computer-assisted review (CAR) Predictive coding Latent semantic analysis Precision Recall The
More informationThree Methods for ediscovery Document Prioritization:
Three Methods for ediscovery Document Prioritization: Comparing and Contrasting Keyword Search with Concept Based and Support Vector Based "Technology Assisted Review-Predictive Coding" Platforms Tom Groom,
More informationPredictive Coding Defensibility and the Transparent Predictive Coding Workflow
WHITE PAPER: PREDICTIVE CODING DEFENSIBILITY........................................ Predictive Coding Defensibility and the Transparent Predictive Coding Workflow Who should read this paper Predictive
More informationE-Discovery Tip Sheet
E-Discovery Tip Sheet Random Sampling In days past, one could look at a body of discovery and pretty well calculate how many pairs of eyeballs would be required to examine and code every document within
More informationPredictive Coding Defensibility and the Transparent Predictive Coding Workflow
Predictive Coding Defensibility and the Transparent Predictive Coding Workflow Who should read this paper Predictive coding is one of the most promising technologies to reduce the high cost of review by
More informationE-Discovery Tip Sheet
E-Discovery Tip Sheet A Painful Discovery Toward the end of last year, I populated the Tip Sheet with a series on collections (see ediscovery Tip Sheet: Taking Up Collections Part 1, Part 2, Part 3, Part
More informationHow It Works and Why It Matters for E-Discovery
Continuous Active Learning for Technology Assisted Review How It Works and Why It Matters for E-Discovery John Tredennick, Esq. Founder and CEO, Catalyst Repository Systems Peer-Reviewed Study Compares
More informationHosted Concordance Andy Kass
Concordance Tip Sheet February 2010 Hosted Concordance Andy Kass Quite a while ago September 2007, in fact I discussed the Internet gateway to LexisNexis Concordance, FYI Server. This tool allows Concordance
More informationJudge Peck Provides a Primer on Computer-Assisted Review By John Tredennick
By John Tredennick CEO Catalyst Repository Systems Magistrate Judge Andrew J. Peck issued a landmark decision in Da Silva Moore v. Publicis and MSL Group, filed on Feb. 24, 2012. This decision made headlines
More informationViewpoint ediscovery Services
Xerox Legal Services Viewpoint ediscovery Platform Technical Brief Viewpoint ediscovery Services Viewpoint by Xerox delivers a flexible approach to ediscovery designed to help you manage your litigation,
More informationReviewing Review Under EDRM Andy Kass
Concordance Tip Sheet January 2012 Reviewing Review Under EDRM Andy Kass Attentive readers of this series may recall that, back in July 2011, I addressed setting up and running a Linear Review in Concordance,
More informationWhat Am I Looking At? Andy Kass
Concordance Tip Sheet August 2013 What Am I Looking At? Andy Kass Discovery is the process of requesting, producing and gleaning documents to substantiate assertions of fact in a case. Review is a deep,
More informationThe Evolution, Uses, and Case Studies of Technology Assisted Review
FEBRUARY 4 6, 2014 / THE HILTON NEW YORK The Evolution, Uses, and Case Studies of Technology Assisted Review One Size Does Not Fit All #LTNY Meet Our Panelists The Honorable Dave Waxse U.S. Magistrate
More informationAn Open Look at Keyword Search vs. Predictive Analytics
877.557.4273 catalystsecure.com ARTICLE An Open Look at Keyword Search vs. Can Keyword Search Be As Effective as TAR? John Tredennick, Esq. Founder and CEO, Catalyst Repository Systems 2015 Catalyst Repository
More informationTraining Questions Andy Kass
Concordance Tip Sheet September 2012 Training Questions Andy Kass Let me start with a disclaimer: I have been training software for a long, long time. A significant amount of training I have done over
More informationEnhancing Document Review Efficiency with OmniX
Xerox Litigation Services OmniX Platform Review Technical Brief Enhancing Document Review Efficiency with OmniX Xerox Litigation Services delivers a flexible suite of end-to-end technology-driven services,
More informationMastering Predictive Coding: The Ultimate Guide
Mastering Predictive Coding: The Ultimate Guide Key considerations and best practices to help you increase ediscovery efficiencies and save money with predictive coding 4.5 Validating the Results and Producing
More informationMaking reviews more consistent and efficient.
Making reviews more consistent and efficient. PREDICTIVE CODING AND ADVANCED ANALYTICS Predictive coding although yet to take hold with the enthusiasm initially anticipated is still considered by many
More informationE-Discovery Tip Sheet
E-Discovery Tip Sheet Redaction Exposed When we talk about reserving material from document production, we generally think about two main strategies: 1. withholding documents under a claim of privilege,
More informationAssisted Review Guide
Assisted Review Guide Version 8.2 November 20, 2015 For the most recent version of this document, visit our documentation website. Table of Contents 1 Relativity Assisted Review overview 5 Using Assisted
More informationTraining Agendas and Pricing
Training Agendas and Pricing Contents 1 Relativity Training Overview... 3 2 Relativity Administrative Training... 5 3 Relativity Analytics Training... 8 4 Relativity Assisted Review Training... 10 5 Relativity
More informationE-Discovery Tip Sheet
E-Discovery Tip Sheet Taking Up Collections, Part 2: Small Office Preservation In our previous conversation we discussed preserving and collecting that most essential cornerstone of corporate information,
More informationPRESENTED BY: Sponsored by:
PRESENTED BY: Sponsored by: Practical Uses of Analytics in E-Discovery - A PRIMER Jenny Le, Esq. Vice President of Discovery Services jle@evolvediscovery.com E-Discovery & Ethics Structured, Conceptual,
More informationPredictive Coding: E-Discovery Game Changer?
PAGE 11 Predictive Coding: E-Discovery Game Changer? By Melissa Whittingham, Edward H. Rippey and Skye L. Perryman Predictive coding promises more efficient e- discovery reviews, with significant cost
More informationCost-Effective and Defensible Technology Assisted Review
WHITE PAPER: SYMANTEC TRANSPARENT PREDICTIVE CODING Symantec Transparent Predictive Coding Cost-Effective and Defensible Technology Assisted Review Who should read this paper Predictive coding is one of
More informationWhitepaper: Enterprise Vault Discovery Accelerator and Clearwell A Comparison August 2012
888.427.5505 Whitepaper: Enterprise Vault Discovery Accelerator and Clearwell A Comparison August 2012 Prepared by Dan Levine, Principal Engineer & Miguel Ortiz, Esq., ediscovery Specialist Globanet 15233
More information2011 Winston & Strawn LLP
Today s elunch Presenters John Rosenthal Litigation Washington, D.C. JRosenthal@winston.com Scott Cohen Director of E Discovery Support Services New York SCohen@winston.com 2 What Was Advertised Effective
More informationElectronically Stored Information: Focus on Review and Strategies
Procrastinators Programs SM Electronically Stored Information: Focus on Review and Strategies Gavin Manes, Ph.D., Avansic Course Number: 0200121220 1 Hour of CLE December 20, 2012 11:20 12:20 p.m. Gavin
More informationAPPENDIX B TO REQUEST FOR PROPOSALS
Overview and Instructions APPENDIX B The service provider s responsibilities will include the following: (A) Processing of ESI produced to CTAG in a variety of file formats; (B) Hosting ESI produced to
More informationPredictive Coding Defensibility
Predictive Coding Defensibility Who should read this paper The Veritas ediscovery Platform facilitates a quality control workflow that incorporates statistically sound sampling practices developed in conjunction
More informationAccessData Corporation. No More Load Files. Integrating AD ediscovery and Summation to Eliminate Moving Data Between Litigation Support Products
AccessData Corporation No More Load Files Integrating ediscovery and Summation to Eliminate Moving Data Between Litigation Support Products White Paper August 2010 TABLE OF CONTENTS Introduction... 1 The
More informationStu Van Dusen Marketing Manager, Lexbe LC. September 18, 2014
Best Practices: Litigation Document Management Applying The Latest Lexbe ediscovery Platform Features and Functionality for Fast and Collaborative Reviews and Productions September 18, 2014 Stu Van Dusen
More informationReview Easy Guide for Administrators. Version 1.0
Review Easy Guide for Administrators Version 1.0 Notice to Users Verve software as a service is a software application that has been developed, copyrighted, and licensed by Kroll Ontrack Inc. Use of the
More informationSoftware-assisted document review: An ROI your GC can appreciate. kpmg.com
Software-assisted document review: An ROI your GC can appreciate kpmg.com b Section or Brochure name Contents Introduction 4 Approach 6 Metrics to compare quality and effectiveness 7 Results 8 Matter 1
More informationTechnology Assisted Review of Documents
Ashish Prasad, Esq. Noah Miller, Esq. Joshua C. Garbarino, Esq. October 27, 2014 Table of Contents Introduction... 3 What is TAR?... 3 TAR Workflows and Roles... 3 Predictive Coding Workflows... 4 Conclusion...
More informationA Practitioner s Guide to Statistical Sampling in E-Discovery. October 16, 2012
A Practitioner s Guide to Statistical Sampling in E-Discovery October 16, 2012 1 Meet the Panelists Maura R. Grossman, Counsel at Wachtell, Lipton, Rosen & Katz Gordon V. Cormack, Professor at the David
More informationTake an Enterprise Approach to E-Discovery. Streamline Discovery and Control Review Cost Using a Central, Secure E-Discovery Cloud Platform
Take an Enterprise Approach to E-Discovery Streamline Discovery and Control Review Cost Using a Central, Secure E-Discovery Cloud Platform A Smarter Approach Catalyst s e-discovery cloud platform provides
More informationOne Decision Document Review Accelerator. Orange Legal Technologies. OrangeLT.com Info@OrangeLT.com
One Decision Document Review Accelerator Orange Legal Technologies OrangeLT.com Info@OrangeLT.com By the Numbers: The Need for Technology in Attorney Review Seventy. Integrated near- duplicate detection
More informationTechnology Assisted Review: Don t Worry About the Software, Keep Your Eye on the Process
Technology Assisted Review: Don t Worry About the Software, Keep Your Eye on the Process By Joe Utsler, BlueStar Case Solutions Technology Assisted Review (TAR) has become accepted widely in the world
More informationThe Next Phase of Electronic Discovery Process Automation
White Paper Predictive Coding The Next Phase of Electronic Discovery Process Automation By Katey Wood and Brian Babineau August, 2011 This ESG White Paper was commissioned by Recommind and is distributed
More informationESI: Focus on Review and Production Strategy. Meredith Lee, Online Document Review Supervisor, Paralegal
ESI: Focus on Review and Production Strategy Meredith Lee, Online Document Review Supervisor, Paralegal About Us Avansic E-discovery and digital forensics company founded in 2004 by Dr. Gavin W. Manes,
More informationMaking The Most Of Document Analytics
Portfolio Media. Inc. 860 Broadway, 6th Floor New York, NY 10003 www.law360.com Phone: +1 646 783 7100 Fax: +1 646 783 7161 customerservice@law360.com Making The Most Of Document Analytics Law360, New
More informationHOW TO BECOME AN ESI HERO
HOW TO BECOME AN ESI HERO taking the mystery out of ediscovery www.fxhnd.com info@fxhnd.com Electronically Stored Information Boo! But why do I have to learn about all this technology? It s how we communicate
More informationREDUCING COSTS WITH ADVANCED REVIEW STRATEGIES - PRIORITIZATION FOR 100% REVIEW. Bill Tolson Sr. Product Marketing Manager Recommind Inc.
REDUCING COSTS WITH ADVANCED REVIEW STRATEGIES - Bill Tolson Sr. Product Marketing Manager Recommind Inc. Introduction... 3 Traditional Linear Review... 3 Advanced Review Strategies: A Typical Predictive
More informationStarter Template. August 14, 2015 - Version 9.2
Starter Template August 14, 2015 - Version 9.2 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
More informationContents. Meltwater Quick-Start Guide
Meltwater Quick-Start Guide Contents Introduction... 2 Meltwater at a Glance... 2 Logging in... 3 Account Management... 3 Searches... 4 Keyword Search... 6 Advanced Search... 7 Source Selections... 9 Inbox...
More informationCapstone for Records Management
Capstone for Records Management Patrick Bland, Esq. ediscovery & Information Governance Specialist DLT Solutions Capstone for Records Management 1 DLT Solutions Company Background Provider of best of breed
More informationESI and Predictive Coding
Beijing Boston Brussels Chicago Frankfurt Hong Kong ESI and Predictive Coding Houston London Los Angeles Moscow Munich New York Palo Alto Paris São Paulo Charles W. Schwartz Chris Wycliff December 13,
More informationwww.pwc.nl Review & AI Lessons learned while using Artificial Intelligence April 2013
www.pwc.nl Review & AI Lessons learned while using Artificial Intelligence Why are non-users staying away from PC? source: edj Group s Q1 2013 Predictive Coding Survey, February 2013, N = 66 Slide 2 Introduction
More informationPr a c t i c a l Litigator s Br i e f Gu i d e t o Eva l u at i n g Ea r ly Ca s e
Ba k e Offs, De m o s & Kicking t h e Ti r e s: A Pr a c t i c a l Litigator s Br i e f Gu i d e t o Eva l u at i n g Ea r ly Ca s e Assessment So f t wa r e & Search & Review Tools Ronni D. Solomon, King
More informationOnly 1% of that data has preservation requirements Only 5% has regulatory requirements Only 34% is active and useful
Page 1 LMG GROUP vs. THE BIG DATA TIDAL WAVE Recognizing that corporations, law firms and government entities are faced with tough questions in today s business climate, LMG Group LLC ( LMG Group ) has
More informationSymantec ediscovery Platform, powered by Clearwell
Symantec ediscovery Platform, powered by Clearwell Data Sheet: Archiving and ediscovery The brings transparency and control to the electronic discovery process. From collection to production, our workflow
More informationIBM ediscovery Identification and Collection
IBM ediscovery Identification and Collection Turning unstructured data into relevant data for intelligent ediscovery Highlights Analyze data in-place with detailed data explorers to gain insight into data
More informationE-discovery Taking Predictive Coding Out of the Black Box
E-discovery Taking Predictive Coding Out of the Black Box Joseph H. Looby Senior Managing Director FTI TECHNOLOGY IN CASES OF COMMERCIAL LITIGATION, the process of discovery can place a huge burden on
More informationAre You Paying Too Much for ediscovery Processing?
Are You Paying Too Much for ediscovery Processing? How new technologies can accelerate ediscovery and lower your costs Guy MacNeill Product Manager, Lexbe LC ediscovery Webinar Series About our webinars
More informationDocument Review Costs
Predictive Coding Gain Earlier Insight and Reduce Document Review Costs Tom Groom Vice President, Discovery Engineering tgroom@d4discovery.com 303.840.3601 D4 LLC Litigation support service provider since
More informationHow to pick ediscovery software
How to pick ediscovery software WWW.CSDISCO.COM How to pick ediscovery software Here, from most important to least, are the factors you should consider in picking ediscovery software: 1 SPEED The most
More informationThe Case for Technology Assisted Review and Statistical Sampling in Discovery
The Case for Technology Assisted Review and Statistical Sampling in Discovery Position Paper for DESI VI Workshop, June 8, 2015, ICAIL Conference, San Diego, CA Christopher H Paskach The Claro Group, LLC
More informationBest Practices: ediscovery Search
Best Practices: ediscovery Search Improve Speed and Accuracy of Reviews & Productions with the Latest Tools February 27, 2014 Karsten Weber Principal, Lexbe LC ediscovery Webinar Series Info & Future Takes
More information2972 NW 60 th Street, Fort Lauderdale, Florida 33309 Tel 954.462.5400 Fax 954.463.7500
2972 NW 60 th Street, Fort Lauderdale, Florida 33309 Tel 954.462.5400 Fax 954.463.7500 5218 South East Street, Suite E-3, Indianapolis, IN 46227 Tel 317.247.4400 Fax 317.247.0044 Presented by Providing
More informationZEROING IN DATA TARGETING IN EDISCOVERY TO REDUCE VOLUMES AND COSTS
ZEROING IN DATA TARGETING IN EDISCOVERY TO REDUCE VOLUMES AND COSTS WELCOME Thank you for joining Numerous diverse attendees Today s topic and presenters This is an interactive presentation You will receive
More informationARCHIVING FOR EXCHANGE 2013
White Paper ARCHIVING FOR EXCHANGE 2013 A Comparison with EMC SourceOne Email Management Abstract Exchange 2013 is the latest release of Microsoft s flagship email application and as such promises to deliver
More informationPredictive Coding Helps Companies Reduce Discovery Costs
Predictive Coding Helps Companies Reduce Discovery Costs Recent Court Decisions Open Door to Wider Use by Businesses to Cut Costs in Document Discovery By John Tredennick As companies struggle to manage
More informationAmazing speed and easy to use designed for large-scale, complex litigation cases
Amazing speed and easy to use designed for large-scale, complex litigation cases LexisNexis is committed to developing new and better Concordance Evolution capabilities. All based on feedback from customers
More informationThis Webcast Will Begin Shortly
This Webcast Will Begin Shortly If you have any technical problems with the Webcast or the streaming audio, please contact us via email at: accwebcast@commpartners.com Thank You! Welcome! Electronic Data
More informationediscovery Technology That Works for You
ediscovery Technology That Works for You Peace of Mind for Serious ediscovery ediscovery demands options, and having one of the industry s most comprehensive portfolios of proprietary and best-of-breed
More informationPredictive Coding, TAR, CAR NOT Just for Litigation
Predictive Coding, TAR, CAR NOT Just for Litigation February 26, 2015 Olivia Gerroll VP Professional Services, D4 Agenda Drivers The Evolution of Discovery Technology Definitions & Benefits How Predictive
More informationWhere the Rubber Meets the Road: The Evolution of ESI Discovery Readiness When IT Resources are Limited
November 17, 2010 Where the Rubber Meets the Road: The Evolution of ESI Discovery Readiness When IT Resources are Limited Wayne Wong, Managing ESI Consultant, Kroll Ontrack Tom McCaffrey, Director of Archiving,
More informationInfoView User s Guide. BusinessObjects Enterprise XI Release 2
BusinessObjects Enterprise XI Release 2 InfoView User s Guide BusinessObjects Enterprise XI Release 2 Patents Trademarks Copyright Third-party contributors Business Objects owns the following U.S. patents,
More informationThe Tested Effectiveness of Equivio>Relevance in Technology Assisted Review
ediscovery & Information Management White Paper The Tested Effectiveness of Equivio>Relevance in Technology Assisted Review Scott M. Cohen Elizabeth T. Timkovich John J. Rosenthal February 2014 2014 Winston
More informationDSi Pilot Program: Comparing Catalyst Insight Predict with Linear Review
case study DSi Pilot Program: Comparing Catalyst Insight Predict with Linear Review www.dsicovery.com 877-797-4771 414 Union St., Suite 1210 Nashville, TN 37219 (615) 255-5343 Catalyst Insight Predict
More informationReduce Cost and Risk during Discovery E-DISCOVERY GLOSSARY
2016 CLM Annual Conference April 6-8, 2016 Orlando, FL Reduce Cost and Risk during Discovery E-DISCOVERY GLOSSARY Understanding e-discovery definitions and concepts is critical to working with vendors,
More informationE- Discovery in Criminal Law
E- Discovery in Criminal Law ! An e-discovery Solution for the Criminal Context Criminal lawyers often lack formal procedures to guide them through preservation, collection and analysis of electronically
More informationBest Practices: Cloud ediscovery Using On-Demand Technology and Workflows to Speed Discovery and Reduce Expenditure
Using On-Demand Technology and Workflows to Speed Discovery and Reduce Expenditure June 11, 2015 Stu Van Dusen Lexbe LC ediscovery Webinar Series Info Future Takes Place Monthly Cover a Variety of Relevant
More informationBest Practices: Defensibly Collecting, Reviewing, and Producing Email
Best Practices: Defensibly Collecting, Reviewing, and Producing Email October 9, 2014 Karsten Weber Principal, Lexbe LC ediscovery Webinar Series Info & Future Takes Place Monthly Cover a Variety of Relevant
More informationVeritas ediscovery Platform
TM Veritas ediscovery Platform Overview The is the leading enterprise ediscovery solution that enables enterprises, governments, and law firms to manage legal, regulatory, and investigative matters using
More informationVoice and data recording Red Box makes it easier than you imagine
Voice and data recording Red Box makes it easier than you imagine SIMPLER SMARTER VOICE If you re reading this, there s a good chance your organization has to record phone calls, radio conversations or
More informationAutonomy Education. Autonomy ediscovery Administrator, Project Manager & End User Training
Autonomy Education Autonomy ediscovery Administrator, Project Manager & End User Training Autonomy ediscovery delivers an innovative approach to ediscovery, through rapid data intake and streamlined processing,
More informationII Workshop University of Pennsylvania Philadelphia, PA
Through A Lawyer s Lens: Measuring Performance in Conducting Large Scale Searches Against Heterogeneous Data Sets in Satisfaction of Litigation Requirements II Workshop University of Pennsylvania Philadelphia,
More informationLexisNexis TotalPatent. Training Manual
LexisNexis TotalPatent Training Manual March, 2013 Table of Contents 1 GETTING STARTED Signing On / Off Setting Preferences and Project IDs Online Help and Feedback 2 SEARCHING FUNDAMENTALS Overview of
More informationWorkflow Solutions for Very Large Workspaces
Workflow Solutions for Very Large Workspaces February 3, 2016 - Version 9 & 9.1 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
More informationImplementing Project Server 2010
Implementing Project Server 2010 Course ISI-1327 4 Days Instructor-led, Hands-on Course Description This instructor-led course will provide you with the knowledge and skills to effectively install and
More informationIntegrated Analytics. Simplified Case Administration
The Difference E-discovery s most complete document review and case management software. NR R Visual Review Ringtail combines powerful keyword search, concept clustering and e-discovery s best, and only,
More informationThe United States Law Week
The United States Law Week Source: U.S. Law Week: News Archive > 2012 > 04/24/2012 > BNA Insights > Under Fire: A Closer Look at Technology- Assisted Document Review E-DISCOVERY Under Fire: A Closer Look
More informationREADY FOR THE MATRIX? MAN VERSUS MACHINE
READY FOR THE MATRIX? MAN VERSUS MACHINE by Laura Ewing Pearle, CEDS Assistant Director, Client Services Cobra Legal Solutions In a 2014 order, Judge Denise Cote presented a Valentine s Day present to
More informationSetting Up Person Accounts
Setting Up Person Accounts Salesforce, Winter 16 @salesforcedocs Last updated: November 4, 2015 Copyright 2000 2015 salesforce.com, inc. All rights reserved. Salesforce is a registered trademark of salesforce.com,
More informationDiscovery of Electronically Stored Information ECBA conference Tallinn October 2012
Discovery of Electronically Stored Information ECBA conference Tallinn October 2012 Jan Balatka, Deloitte Czech Republic, Analytic & Forensic Technology unit Agenda Introduction ediscovery investigation
More informationChristina Wojcik, VP Legal Services, Seal Software Steven Toole, VP Marketing, Content Analyst Company Jason Voss, Senior Product Manager, TCDi
FEBRUARY 3 5, 2015 / THE HILTON NEW YORK ML1: Machine Learning Powered Rapid Insight into Big Content: Discovery from Contracts to Patents to Litigation Panelists Christina Wojcik, VP Legal Services, Seal
More informationMailTags 4. Quick Start Guide V: 4.0
MailTags 4 Quick Start Guide V: 4.0 Introductions What is MailTags? MailTags is the indispensable enhancement to Apple s Mail application to help you turn email chaos into email order. With MailTags you
More informationIntroduction to Predictive Coding
Introduction to Predictive Coding Herbert L. Roitblat, Ph.D. CTO, Chief Scientist, OrcaTec Predictive coding uses computers and machine learning to reduce the number of documents in large document sets
More informationWhite Paper Technology Assisted Review. Allison Stanfield and Jeff Jarrett 25 February 2015. 1300 136 993 www.elaw.com.au
White Paper Technology Assisted Review Allison Stanfield and Jeff Jarrett 25 February 2015 1300 136 993 www.elaw.com.au Table of Contents 1. INTRODUCTION 3 2. KEYWORD SEARCHING 3 3. KEYWORD SEARCHES: THE
More informationData Mining. SPSS Clementine 12.0. 1. Clementine Overview. Spring 2010 Instructor: Dr. Masoud Yaghini. Clementine
Data Mining SPSS 12.0 1. Overview Spring 2010 Instructor: Dr. Masoud Yaghini Introduction Types of Models Interface Projects References Outline Introduction Introduction Three of the common data mining
More informationThe Business Case for ECA
! AccessData Group The Business Case for ECA White Paper TABLE OF CONTENTS Introduction... 1 What is ECA?... 1 ECA as a Process... 2 ECA as a Software Process... 2 AccessData ECA... 3 What Does This Mean
More informationLitigation Solutions insightful interactive culling distributed ediscovery processing powering digital review
Litigation Solutions i n s i g h t f u l i n t e r a c t i ve c u l l i n g d i s t r i b u t e d e d i s cove r y p ro ce s s i n g p owe r i n g d i g i t a l re v i e w Advanced Analytical Review Data
More informationData Targeting to Reduce EDVERTISING Costs
Zeroing In, Data Targeting to Reduce ediscovery Volumes and Costs Thursday, September 10th, 2015 Matthew Verga, Director of Content Marketing and ediscovery Strategy Modus ediscovery ACEDS Membership Benefits
More informationHighly Efficient ediscovery Using Adaptive Search Criteria and Successive Tagging [TREC 2010]
1. Introduction Highly Efficient ediscovery Using Adaptive Search Criteria and Successive Tagging [TREC 2010] by Ron S. Gutfinger 12/3/2010 1.1. Abstract The most costly component in ediscovery is the
More informationEnterprise Email Archive Managed Archiving & ediscovery Services User Manual
Enterprise Email Archive Managed Archiving & ediscovery Services User Manual Copyright (C) 2012 MessageSolution Inc. All Rights Reserved Table of Contents Chapter 1: Introduction... 3 1.1 About MessageSolution
More informationThe Truth About Predictive Coding: Getting Beyond The Hype
www.encase.com/ceic The Truth About Predictive Coding: Getting Beyond The Hype David R. Cohen Reed Smith LLP Records & E-Discovery Practice Group Leader David leads a group of more than 100 lawyers in
More information