By Arno R. Lodder, Anja Oskamp
This is able to truly be the worst publication i have ever learn. The upside is that there are 22 pages of bibliography, which took the studying pages right down to 176. If this publication is how the know-how international is making an attempt to get "conservative" legal professionals to replace, then they may besides quit simply because i would particularly learn my Con legislations publication two times than this e-book. This publication is sweet for IT humans short of an realizing of AI within the criminal box, of which there's nearly none. A attorney who wants to enforce IT into her enterprise could have no need for this ebook. it sounds as if the editors bought to the top in their learn and determined to move forward and positioned anything jointly that they can cost 90 cash for.
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Extra info for Information Technology and Lawyers: Advanced Technology in the Legal Domain, from Challenges to Daily Routine
Sample text
And (ii) is the subject of efforts that are reasonable under the circumstances to maintain its secrecy. Section 757 defines a trade secret in Comment b: A trade secret may consist of any formula, pattern, device or compilation of information which is used in one’s business, and which gives him an opportunity to obtain an advantage over competitors who do not know or use it. Comment b elaborates upon this statement: An exact definition of a trade secret is not possible. Some factors to be considered in determining whether given information is one’s trade secret are: 1.
Some researchers have attempted to improve the nearest neighbor approach by employing a weighted distance metric that assigns weights to the different fact descriptors. See, for example, Popple (1993, pp. 62–78, 92–98) and the projects described there. One problem with this approach is that a fact descriptor’s “weight is highly contextual and depends on individual problem situations” (Ashley, 1990, p. 175). In comparing cases, it is important to take into account the particular circumstances of the problem and cases, the relevant similarities and differences and the legal reasons to which they give rise.
It cannot infer from the retrieved cases how the problem should be decided, nor can it make arguments for and against such inferences. A Lexis/Westlaw type system does not even “know” which side won a case or with respect to which claims or issues. Nor can full-text legal information support prediction of outcomes. Given current technology, a legal IR system is not guaranteed to return cases involving the relevant claim and issue, much less to demonstrate a boundary between PRO and CON cases, or other information useful for making arguments or predictions automatically.