This page will provide you with an overview of the concepts of searching, filtering, and evaluating in legal research.
At the end of this lesson you should be able to:
Boolean - a system for representing logical statements, often called "Terms and Connectors" on legal research systems.
Natural Language (NL) - in theory, the ability of a system to understand human speech. In reality, a search mode that permits normal human language in a search query. The system processes the NL query to attempt to understand the question and return relevant results. Results of NL searches are often fixed in number and ranked by relevancy.
Semantic Searching - A proprietary algorithm which parses the words a user types in the search box, and adding other search mechanisms such as relevancy ranking, citation analysis, automatic synonym generation, and more.
Syntax - the structure and order of all the elements in a query (i.e., the order of terms and connectors).
AND - A Boolean connector for a mandatory term (e.g.,
fall AND sidewalk will only find cases that contain both words)
OR - A Boolean connector for an optional term, often used to connect synonyms (e.g.,
slip OR fall OR trip will find cases that contain any of those words)
NOT - A Boolean connector for a term that should be excluded (e.g.,
fall NOT ice will find cases involving falls that do not contain the word ice)
AND NOT - Lexis' version of the NOT connector (note: Lexis wisely suggests that a NOT connector be at the end of your search)
& - alternate way to express the AND connector
% - alternate way to express the NOT / BUT NOT connector in Westlaw
/n - A proximity connector for a mandatory term that must appear within n words of the first term. (e.g., slip /5 ice will only find cases that contain a phrase that contains both terms separated by 5 or fewer terms). Note that /n can be replaced with /s to restrict to the same sentence, or /p to restrict to the same paragraph.
near/n - A proximity connector for a mandatory term that must appear within n words of the first term, and the order of the terms is flexible.
Nearly all searches will involve multiple facts and/or concepts. Our slip and fall example involves at least three different concepts, and we need cases that include them all: a slip/fall injury, on icy or slippery surface, on a business' property.
With a Venn diagram, you can see how these three concepts overlap in multiple ways:
At each of the four overlapped areas, we find a different set of cases:
Your searches need to be constructed with these overlaps in mind.
When you build a search query, you're telling the system which concepts are critical for you.
Begin with a short query, and build by adding connectors. The "OR" connector is permissive: use it to separate synonyms or related concepts, of which you'd accept either. The "AND" connector is a requirement that the term that follows be included in all results.
(slip OR fall) AND (business premises) AND (icy OR slippery)
This example allows for cases to use the term slip OR the term fall to describe the incident. It requires that cases use the phrase "business premises." And then it requires that cases use either the term icy OR the term slippery.
Once you see your results, you can (should) consider revising the search with more ANDs to reduce the number of results, or more ORs to increase the number. A better search might alter the middle set of terms to (business or store or premises), for example. You may need to repeat this process several times, especially throughout your first year.
Building an effective search query requires an understanding of the language likely to be used in the documents you seek. If you have a limited understanding of premises liability issues, for example (perhaps not even being familiar with that term), it may take more iterations of your search query.