Posts Tagged ‘legal’

Cognitum Points To Use Cases For Semantic Knowledge Engineering

fl24Cognitum’s year got off to a good start, with an investment from the Giza Polish Ventures Fund, and it plans to apply some of that funding to building its sales and development teams, demonstrating the approaches to and benefits of semantic knowledge engineering, and focusing on big implementations for recognizable customers. The company’s products include Fluent Editor 2 for editing and manipulating complex ontologies via controlled natural language (CNL) tools, and its NLP-fronted Ontorion Distributed Knowledge Management System for managing large ontologies in a distributed fashion (both systems are discussed in more detail in our story here). “The idea here is to open up semantic technologies more widely,” says CEO Pawel Zarzycki.

To whom? Zarzycki says the company currently has pilot projects underway in the banking sector, which see opportunities to leverage ontologies and semantic management frameworks that provide a more natural way for sharing and reusing knowledge and expressing business rules for purposes such as lead generation and market intelligence. In the telco sector, another pilot project is underway to support asset management and impact assessment efforts, and in the legal arena, the Poland-based company is working with the Polish branch of international legal company Eversheds on applying semantics to legal self-assessment issues. Having a semantic knowledge base can make it possible to automate the tasks behind assessing a legal issue, he says, and so it opens the door to outsourcing this job directly to the entity pursuing the case, with the lawyer stepping in mostly at the review stage. That saves a lot of time and money.

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Semantic Tech’s Growing Influence In The E-Discovery Market

Photo Courtesy: Flickr/srqpix

The e-discovery market is a growing one, with Gartner this year estimating electronic data discovery software sales will reach $2.9 billion by 2017. The same research firm just recently positioned where vendors fall in that space, with the release of its Magic Quadrant for E-Discovery software.

As recounted here, semantic technology is becoming an increasingly important part of the package; semantic inventory tools, for example, allow for better understanding the vocabulary of litigation and involve repetition in the process of looking for the relevant evidence.

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A Chat With Gartner About Semantic Tech Earning A Spot As Top Tech Trend In 2013

Earlier this month Gartner named semantic technologies to its top ten trends list (see our story here). Recently, we caught up with Gartner vp and distinguished analyst Debra Logan, the lead author on the semantic technologies section of the Top 10 Technology Trends Impacting Information Infrastructure, 2013, to learn more about sem tech’s earning a place on the list.

One interesting point Logan made is that the top ten trends list actually is a reflection of inquiries Gartner sees from its end-user clients. So, semantic technologies’ spot on the list would seem to indicate a bubbling-up of real-world, enterprise interest. As Logan sees it, it’s very much about information overload, about minimizing the risk and maximizing the value of the data on their hands, and about the availability now from providers like Amazon and Google of infrastructures for analyzing Big Data sets.

“If we could get the same meaning from data, we might actually know what is going on, because we sure don’t now,” says Logan, of the quandary facing enterprise IT leaders. “They are struggling with definition issues and reconciliation because of the proliferation of different IT systems.”

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Crowdsourcing the Law

David Meyer of GigaOM reports that Finland is going to use crowdsourcing to create new laws. He writes, “Who makes laws? In most of the democratic world, that’s the sole preserve of elected governments. But in Finland, technology is about to make democracy significantly more direct. Earlier this year, the Finnish government enabled something called a “citizens’ initiative”, through which registered voters can come up with new laws – if they can get 50,000 of their fellow citizens to back them up within six months, then the Eduskunta (the Finnish parliament) is forced to vote on the proposal.” Read more

Legally Linked: Linked Open Data Principles Applied To Code Of Federal Regulations

The Legal Information Institute at Cornell University Law School is about making law accessible and understandable, for free. It’s been engaged in that mission since the early ’90s, and semantic web technology today plays a role in furthering that goal.

The organization this month published a new electronic edition of the Code of Federal Regulations (CFR), which contains a bevy of rules across 50 titles that impact nearly all areas of American business. Work underway at LII, dubbed the Linked Legal Data project, seeks to apply Linked Open Data principles enhances access to the CFR, with capabilities such as  being able to search its Title 21 Food and Drugs database using brand names for drugs (such as Tylenol), and receiving the generic name for the drug (acetaminophen) as a suggested term. “You cannot look for regulatory information on Tylenol in the CFR because Tylenol will never be there,” says Dr. Núria Casellas, who is a visiting scholar at the LII spearheading work on the project. “That is a brand name. What you actually want to look for are components, such as acetaminophen.”

While the general citizenry might find reasons to leverage the fruits of this effort, businesses that must comply with these requirements are a more likely target – not just the lawyers and paralegals, but those responsible for tasks, for example, such as storing and caring for products their company exports or imports, including understanding the safety regulations that apply to it. The Tylenol-acetaminophen example, she says, is very interesting because it showcases how using the wrong word or the incorrect approach can hamper a company from being able to find the relevant regulatory or safety information it needs to take into consideration.

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Semantic Tech Can Take Pain Out Of eDiscovery

Last month Magistrate Judge Andrew Peck, of the U.S. District Court for the Southern District of New York, issued an opinion in a gender discrimination case that had this to say about computer-assisted review: “Computer-assisted review is an available tool and should be seriously considered for use in large-data-volume cases where it may save the producing party (or both parties) significant amounts of legal fees in document review.”

In doing so, he just also may have made a case for the legal profession to do some more investigation of semantic technology in order to cope with its own Big Data challenges. In the mid-2000s, the Federal Rules of Civil Procedure were amended to take into account electronic discovery, so that both sides in a legal challenge would have to confer within sixty days of filing to disclose how they handled digital data. The beauty of the American legal system is that it requires each party to pony up information that is meaningful and responsive to the facts of the case. The dark side is that the proliferation of data inside businesses means employees are creating more and more data in lots of different ways, which means legal staff has to spend a lot more time sifting through digital realms of structured and unstructured information to discover what may have to do with a lawsuit or government investigation, what is responsive to the other party’s document request, and what is privileged information, too.

“It’s created a cottage industry in temp staffing – now there are temp lawyers, contract attorneys who work from $30 to $75 an hour,” says Jay Leib, Chief Strategy Officer at kCura, which makes the Relativity Assisted Review e-discovery text analytics software based on latent semantic indexing technology. “Just like we outsource factory workers, there are outsourced attorneys overseas doing document review to combat the amount of data that’s sprung up.” There is so much data out there that it’s entirely possible that a $3 million lawsuit could cost $6 million to litigate, he says.

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Digital Reasoning To Give Users New Tool For “Learning” Custom Data Sets

Digital Reasoning, developers of the Synthesys platform for discovering the meaning in unstructured data at scale, has on the roadmap exposing to and packaging up for its customers a simplified version of its internal technology for teaching the system new grammatical structures so that it can quickly understand custom or otherwise specific data sets.

The company has quickly added support for new languages such as Arabic, traditional and simplified Chinese, Farsi and Urdu (with more languages on the way) to Synthesys using the tool. The tool gets the software up to speed on each one in just a few weeks by teaching it the grammatical structure and then letting it go off and figure out what the words mean for its work of transforming unstructured (and structured) data into the underlying facts, entities, relationships, and associated terms.

“In the same way we teach it languages you may have a data set that is highly scientific, for example, and this tool essentially makes it easier for our customers to make Synthesys even more accurate for that specific set of data,” says Dave Danielson, VP of marketing.

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