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Information Analysis and Repackaging

Notes jargon, polysemes (words that have different meanings when used in a legal context), and constant
change.

Techniques used to achieve these goals generally fall into three categories: Boolean
retrieval, manual classification of legal text, and natural language processing of
legal text.

Problems

Application of standard information retrieval techniques to legal text can be more difficult than
application in other subjects. One key problem is that the law rarely has an inherent taxonomy. Instead,
the law is generally filled with open-ended terms, which may change over time. This can be especially
true in common law countries, where each decided case can subtly change the meaning of a certain
word or phrase.
Legal information systems must also be programmed to deal with law-specific words and phrases.
Though this is less problematic in the context of words which exist solely in law, legal texts also
frequently use polysemes, words may have different meanings when used in a legal or common-
speech manner, potentially both within the same document. The legal meanings may be dependent
on the area of law in which it is applied. For example, in the context of European Union legislation,
the term “worker” has four different meanings:
Any worker as defined in Article 3(a) of Directive 89/391/EEC who habitually uses display screen
equipment as a significant part of his normal work.
Any person employed by an employer, including trainees and apprentices but excluding domestic
servants;
Any person carrying out an occupation on board a vessel, including trainees and apprentices, but
excluding port pilots and shore personnel carrying out work on board a vessel at the quayside;
Any person, who, in the Member State concerned, is protected as an employee under national
employment law and in accordance with national practice;
In addition, it also has the common meaning:
A person who works at a specific occupation.
Though the terms may be similar, correct information retrieval must differentiate between the
intended use and irrelevant uses in order to return the correct results.
Even if a system overcomes the language problems inherent in law, it must still determine the
relevancy of each result. In the context of judicial decisions, this requires determining the precedential
value of the case. Case decisions from senior or superior courts may be more relevant than those
from lower courts, even where the lower court’s decision contains more discussion of the relevant
facts.
The opposite may be true, however, if the senior court has only a minor discussion of the topic (for
example, if it is a secondary consideration in the case). A information retrieval system must also be
aware of the authority of the jurisdiction. A case from a binding authority is most likely of more
value than one from a non-binding authority.
Additionally, the intentions of the user may determine which cases they find valuable. For instance,
where a legal professional is attempting to argue a specific interpretation of law, he might find a
minor court’s decision which supports his position more valuable than a senior courts position
which does not. He may also value similar positions from different areas of law, different jurisdictions,
or dissenting opinions.
Overcoming these problems can be made more difficult because of the large number of cases
available. The number of legal cases available via electronic means is constantly increasing (in 2003,

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