In a legal setting, it is frequently important to retrieve all information related to a specific query.
[4] Legal Information Retrieval attempts to increase the effectiveness of legal searches by increasing the number of relevant documents (providing a high recall rate) and reducing the number of irrelevant documents (a high precision rate).
[7] This can be especially true in common law countries, where each decided case can subtly change the meaning of a certain word or phrase.
Even if a system overcomes the language problems inherent in law, it must still determine the relevancy of each result.
[10] 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).
The number of legal cases available via electronic means is constantly increasing (in 2003, US appellate courts handed down approximately 500 new cases per day[2]), meaning that an accurate legal information retrieval system must incorporate methods of both sorting past data and managing new data.
[12] In order to overcome the limits of basic boolean searches, information systems have attempted to classify case laws and statutes into more computer friendly structures.
Additionally, both of these services allow browsing of their classifications, via Westlaw's West Key Numbers[14] or Lexis' Headnotes.
[17] The legal texts included, however, were carefully controlled to just a few areas of law in a specific jurisdiction.
[18] The major drawback to this approach is the requirement of using highly skilled legal professionals and large amounts of time to classify texts.
[16][19] As the amount of text available continues to increase, some have stated their belief that manual classification is unsustainable.
[2][21][22] Adequate translation of both would allow accurate information retrieval without the high cost of human classification.