Un-Legislative History

Wikipedia is often a boon for quick legal research about well-publicized matters.  It’s a great way to find where a statute is codified, or the background of a famous case.  When it comes to legislative history, though, sometimes Wikipedia’s a bust.  For anyone looking for a good example of why one must follow up with proper research into legislative history, please see Wikipedia’s entry on the Dodd-Frank Wall Street Reform and Consumer Protection Act, which passed in July 2010.  As of Nov. 16, 2010, Wikipedia has the following to say about the changes implemented by Title XI of Dodd-Frank:

“The Federal Reserve Act is amended to change the New York Federal Reserve President to a Presidential appointment, with the advice and consent of the Senate.”

In support of this assertion, Wikipedia cites and links to the Enrolled Final Version of HR 4173, available on the LOC’s Thomas page.  Unfortunately, Wikipedia gets it wrong:  The version of the bill that passed Congress removed that language (which had been proposed by the Senate but rejected by the House).  The Senate’s proposal in this regard was snipped on June 17, 2010, weeks before the final bill passed.  Legislative history research–including review of committee meeting transcripts–coupled with news and secondary source coverage bore out the truth.

We always offer cautions when it comes to Wikipedia, and now there’s a handy example to which we can refer.

UPDATE:  Thanks to our helpful reader, Wikipedia has been policed. . .while its lesson remains!

Bloomberg Law, LexisNexis, Westlaw — New, Improved

From today’s New York Times:

The New York Times, Monday, January 25, 2010, p. B5

Technology

Legal Sites Plan Revamps As Rivals Undercut Price

By Ashlee Vance

Westlaw and LexisNexis, the dominant services in the market for computerized legal research, will undergo sweeping changes in a bid to make it easier and faster for lawyers to find the documents they need.

And in the February issue of the ABA Journal:

Legal Technology
Exclusive: Inside the New Westlaw, Lexis & Bloomberg Platforms
By Jill Schachner Chanen

After decades of Westlaw and Lexis rolling out incremental improvements, real innovation has become the watchword in online legal research. At stake: billions in revenue and a big piece of your computer desktop.

The ABA Journal article quotes yours truly.   A point I was trying to make, but it didn’t make the article, was how useful I find added features such as Westlaw’s ResultsPlus and Lexis’s Related Content.  These features steer students to what could be very valuable secondary source material that they wouldn’t necessarily think to search since many have the inclination to jump feet first into the case law databases.

New article on West Publishing

From the November 2009 issue of Twin Cities Business:  “Thomson Reuters’ Brain,” by Dave Beal

The Eagan business that was once West Publishing now supplies its parent company with the intellectual firepower to outmaneuver Bloomberg and LexisNexis in the financial and legal content wars.

Lede:

There may be no more concise way to sum up the changed nature or ambitions of the former West Publishing Company than what Roger Martin says:  “We are sort of the next generation of Google — without the garbage — for professionals.”

The article discusses how successful the legal division is for the company:

Legal . . . is just one of seven primary business units . . . , but it’s a big contributor to the bottom line.  In 2008, it accounted for 27 percent of Thomson Reuter’s $ 13.4 billion in revenue and 39 percent of its operating income. . . .   In the first quarter of 2009, the legal unit had an operating margin of 32.1 percent versus 20.7 percent for the entire company. . . .

The article goes on to discuss the work of the company’s many “information technologists” and quotes chief scientist Peter Jackson on “the right balance of natural and artificial intelligence is a product-development key.”

One such product is ResultsPlus, which I have found extremely useful at time.  Acccording to the article,

ResultsPlus is built on machine learning and natural language processing, . . . but also central to its effectiveness is that it uses the primary search results — those guided by the user — to shape the secondary search. (The “metadata” fed into the secondary search also include “West key numbers,” . . . ).

Other sections of the article include:

Thomson Sells Reuters and Vice Versa

An Edge on LEXISNEXIS?

Westlaw’s war with LexisNexis has shifted back and forth for a generation, since a version of LexisNexis launched in 1973, two years ahead of Westlaw.  Lately, the clash is tilting in Westlaw’s favor.

Battling BLOOMBERG: Terminals, News, and Datafeeds

The article concludes:

Given potential growth in emerging markets and more opportunities being generated by Jackson’s R&D group, [Peter] Warwick [CEO of Thomson Reuters Legal] puts the annual revenue potential of the legal division alone at $ 14.3 billion — four times Thomson’s Reuters Legal’s revenues in 2008.

But growth will depend on how adept the company is at continuing to add value to its massive collections of data.  Google searches, after all, are free; Thomson Reuters is a Google for professionals who are willing to ante up for it.  As the company . . . has discovered, information itself is merely a commodity in the information age.  Information as a service — infinitely searchable, sortable, and customizable — is what’s in demand.

Is searching the best way to retrieve legal documents?

This paper from Norway suggests that legal information sources ” have a rich and homogeneneous structure which makes it possible to establish chronological, alphabetical and systematic indexes,” something we tell our students over and over and over again.

Is searching the best way to retrieve legal documents?

By Trygve Harvold

Lov&Data nr. 98 – Juni 2009

Abstract:

Legal texts have a rich structure and a large number of links which can be utilized in retrieving documents.  This paper is based on a numerical study of the link structure in approximately 200,000 documents in the Lovdata database.  The hypertext structure is analyzed and it is suggested that it should be possible to navigate the database on the basis of indexes and links.  Analysis of the use of Lovdata also indicated that utilizing chronological and alphabetical indexes and the hyperstructure of links might in many cases be a more efficient and use-friendly way of finding documents than the traditional search.

 

Conclusion:

While searching is a necessary and powerful tool, it may not always be the most user-friendly way of locating documents in a legal information system.  In this paper we have shown how the rich structure and numerous links of legal documents allow for the construction of indexes, buttons and links which makes it possible for users to navigate the system without searching.  User statistics from Lovdata show that users often prefer this alternative way of navigation in situations where it is possible and practical.

 

The paper is rich with persuasive illustrations.

Twoogle and Twofind

Maybe this isn’t news to our web savvy readers, but I recently twumbled upon (err, stumbled upon while on twitter) two nifty search tools:  Twoogle and Twofind

Both Twoogle and Twofind are brought to us by Browsys.    And, both tools allow for simultaneous searching. 

In the case of Twoogle, user can search Twitter and Google at the same time.  The results are displayed split-screen, with Google results on one side and Twitter on the other.  And, for fun, you can click “Tweet Results” if you’d like to share what you find on Twitter.    Pretty simple, but very practical.

And, Twofind allows users to search across two different search engines with the same split-screen display.  The default is for Google and Bing searching, but you can search across any combination of Google, Bing, Yahoo,  and Twitter.

Aardvark’s Answer Machine

Typing a question  into a search engine and getting a specific, relevant answer hasn’t improved much since the 1957 librarian-favorite film Desk Set when EMMARAC (the Electromagnetic Memory and Research Arithmetical Calculator) answered a question about Watusis and the island of Corfu with Rose Hartwick Thorpe’s poem Curfew Must Not Ring Tonight.  Make it a subjective question, e.g., “What  is the best Chinese restaurant in Palo Alto?,” and the results are even less helpful, as noted in a “Digital Domain” article by Randall Stross in today’s New York Times.  The article, “Now All Your Friends Are in the Answer Business,” discusses “Aardvark . . . a Web service that answers users’  questions through their friends and friends-of-friends.”

Often at the reference desk I don’t answer a patron’s question but, instead, seek to find someone who can provide a good answer — I’m more a  switchboard operator than fountain of knowledge.  So Aardvark’s approach of using networks to make the connection between question and human-supplied answer is intriguing.  As the article explains,

A new service offered by Aardvark (vark.com), however, provides specific recommendations. Its advice is always current, too, obtained on the fly from those we trust, like friends, but whose collective expertise far exceeds that of the relatively few people we happen to know personally.

Founded in 2007 and based in San Francisco, the company has just completed beta testing of its answer service and opened it to the public last week. It begins with the social network that you’ve established elsewhere. Presently, it requires Facebook; other networks will be added, it says.

. . .

Aardvark may come to be preferred over answer databases and “decision engines” if many people want a speedy answer from a fellow human being.

My need for a “focus assistant.”

Can technology offer us “continuous augmented awareness?”

An earlier post here, commenting upon an article a year ago in The Atlantic, asked, “Is Google making us stoopid?”  Now an article in the July / August 2009 issue of the same magazine asks, “Is Google actually making us smarter?”

The article, “Get Smart,” by Jamais Cascio, discusses how Twitter can help us move from a world of “continuous partial attention” to one of “continuous augmented awareness.”  I’m a fan of Twitter but I find it hard to quickly sift through tweets about pancakes to the ones that provide truly valuable and timely information (not that pancakes aren’t important, but I use Twitter mainly for work).  Here’s what Mr. Cascio writes:

But imagine if social tools like Twitter had a way to learn what kinds of messages you pay attention to, and which ones you discard. Over time, the messages that you don’t really care about might start to fade in the display, while the ones that you do want to see could get brighter. Such attention filters–or focus assistants–are likely to become important parts of how we handle our daily lives. We’ll move from a world of “continuous partial attention” to one we might call “continuous augmented awareness.”

The article suggests that:

The trouble isn’t that we have too much information at our fingertips, but that our tools for managing it are still in their infancy.

Legal Ontologies Spin a Semantic Web

Legal Ontologies Spin a Semantic Web
By Dr. Adam Z. Wyner
Special to Law.com
June 8, 2009

“The Semantic Web, an extension of the current www, promises to make documents meaningful to people and computers by changing how legal knowledge is represented and managed. Dr. Adam Z. Wyner explains how legal ontologies will help complete the new Web’s design.”

From the article:

ONTOLOGY FOR CASE LAW

Consider an example ontology for case law. There are various approaches to find relevant case law — using text-mining software, search tools, proprietary indices or legal research summaries. These approaches can extract some latent linguistic information from the text but often require researchers to craft the results; indeed, successful information extraction depends on an ontology, and as there is not yet a rich ontology of the case law domain, much information in cases cannot be easily extracted or reasoned with. Moreover, none of these approaches apply inference rules.

Reading a case such as Manhattan Loft v. Mercury Liquors, there are elementary questions that can be answered by any legal professional, but not by a computer:

Where was the case decided?
Who were the participants and what roles did they play?
Was it a case of first instance or on appeal?
What was the basis of the appeal?
What were the legal issues at stake?
What were the facts?
What factors were relevant in making the decision?
What was the decision?
What legislation or case law was cited?

Legal information service providers such as LexisNexis index some of the information and provide it in headnotes, but many of the details, which may be crucial, can only be found by reading the case itself. Current text-mining technologies cannot answer the questions because the information is embedded in the complexities of the language of the case, which computers cannot yet fully parse and understand. Finally, there are relationships among the pieces of information which no current automated system can represent, such as the relationships among case factors or precedential relationships among cases.

In conclusion, the author remarks:

Legal ontologies are one of the central elements of managing and automating legal knowledge. With ontologies, the means are available to realize significant portions of the Semantic Web for legal professionals, particularly if an open-source, collaborative approach is taken.

 

About the author:

Dr. Adam Zachary Wyner is affiliated with the department of computer science at University College London, London, United Kingdom. He has a Ph.D. in linguistics from Cornell University and a Ph.D. in computer science from King’s College London. He has published on topics in the syntax and semantics of natural language, as well as artificial intelligence and law concerning legal systems, language, logic and argumentation. For further information, see Dr. Wyner’s blog LanguageLogicLawSoftware.

Source: Law.com – Daily Newswire

Bing for travel

As many of us make summer travel plans, I learned about a feature of the new search engine Bing that might be useful.

In today’s Wall Street Journal Katherine Boehret “reviews Microsoft’s new search engine, Bing, which offers related content suggestions, a ‘hover’ option that shows a brief snap shot of web pages, and easy navigation of restaurant and travel information.”

The Wall Street Journal, Wednesday, June 3, 2009, p. D1

The Mossberg Solution

Microsoft Effort To Best Google Yields Results

Bing Search Engine is Snazzy, Provides User-Friendly Links; Roger Federer, the Bare Facts

By Katherine Boehret

For people looking up airline flights, Microsoft integrates a technology called Bing Travel into the search.  This tool predicts whether a fare will go up or down in the future based on data aggregation and analysis.  A built-in tool works similarly with hotels, analyzing data to tell if you’re getting a good deal.

Katherine Boehret’s look at Bing is available at:

WSJ.com/PersonalTech

Wolfram Alpha, Kumo and Google Squared

Good article in the Comment & Analysis section of today’s Financial Times, ” Wolfram Alpha asks some searching questions of the web,” by John Gapper.

The article points out that “[w]hile search engines are a starting point in a quest to find things out, Wolfram Alpha provides complete answers.”  Or attempts to, anyway.  According to the article, Wolfram Alpha is especially successful when dealing with “scientific and mathematical data, or the sort of information held routinely on public databases such as . . . World Factbook . . . “

Unlike other search engines, Wolfram Alpha’s data “are not drawn from the web but from a database that is ‘curated’ by Wolfram Research.  . . . Its data are drawn only from sources that are edited and checked . . . “

The article also reports that next week Microsoft will launch what is codenamed Kumo, a search engine to compete with Google.

There’s more on a new Google feature  too:

. . . “One of the hardest problems in computer science is data extraction.  Can we look at the unstructured web and extract values and facts in a meaningful way?” asked [Google's] Marissa Mayer, . . .

Ms. Mayer showed off Google Squared, an experimental new feature that would allow Google users . . . to assemble data about, for example, various breeds of small dogs in a form like a spreadsheet.