By Tisha Davis, Derek Ametam and Joe Wanzala 

This is the seventh installment in our series on dtSearch.  In this installment, we will explore how to leverage dtSearch’s ‘Search Within these Results’ feature to “drill down” or refine your search results.  You can find the previous installments here:  Part 1, Part 2, Part 3, Part 4, Part 5 and Part 6

In today’s litigation, we often get voluminous amounts of discovery on a rolling basis.  Linear review of those discovery productions can result in going down multiple rabbit holes before we find the relevant, useful information. 

As we mentioned in earlier installments, dtSearch is a good search and retrieval tool built to help users quickly find relevant information in massive datasets.  You may have an idea on what names, keywords, terms, or phrases you want to search for.  You may think that you need to run each search separately.  This approach, while good-intentioned, could lead to you spending extra time reviewing duplicative results.  This can be especially time-consuming in cases with lots of data.

Using the “Search Within a Search Feature”

Consider, for example, you are reviewing the results of an earlier search you ran for your client, Tucker Jones. You searched for “Tucker Jones” but now you want to see how many of your current results also reference an injury since that is relevant to your case.  You could rerun the search as a Boolean AND search using the term “injury”. Another option is to refine your initial search using the Search within these results function (see Figures 1 and 2), which will refine the previous search:

• Run a primary search for “Tucker Jones” (26 files, 146 hits).
• Refine that search by searching “injury” within those results (7 files, 20 hits[1]).

This is the same number of resulting files as searching for both terms as an AND Boolean search.

Figure 1.

Figure 2.

Let’s imagine this on a larger scale that involves multiple discovery productions.  Consider the following example:

You are working on a multi-defendant fraud case involving multiple victims. The government has produced in discovery hundreds of gigabytes of data including emails, Microsoft Office files, and PDFs. You want to find all the documents relating to your client, John Smith.  During your review, you come across the name “Sally Williams” and her company “Omega Realty.”  The government has alleged that Sally Williams is a victim of the alleged fraud. You want to  learn more about the relationship between Sally Williams and your client, so you want to find  documents that mention your client as well as Sally Williams or her company.

You have several ways to move forward here. 

• You could run the following search: (John) Smith or (Sally) Williams or “Omega Realty”. This would yield all documents that reference each of those terms.

However, your search results may return tens of thousands of documents. You would have to review the results of each search query to determine how much overlap there is between the sets of results.

• You could also run that query as a new, separate Boolean search e.g., John Smith AND Sally Williams AND Omega Realty. This would return only the documents that mention all three names. This collection is more likely to yield documents where the three names are associated with each other.

• You could then drill down conduct refined searches into the subset of documents using “Search Within these Results” to search for Williams AND “Omega Realty”, or a proximity search, e.g. Smith w/5 of “Omega Realty” for closer associations.

This iterative approach lets you quickly refine your search results and obtain the smaller subset of data that relates to John Smith and Sally Williams’ business dealings invosallylving Omega Realty.

The “Search Within these Results” feature works similarly to the searching that can be done in eDiscovery platforms such as Casepoint or Everlaw. Those platforms let you edit your searches so you can refine or drill-down to narrow down your results to the set that is most pertinent to your search query.

Conclusion

dtSearch is a great  tool for searching for relevant information within large datasets. From basic Boolean and proximity searches to advanced features like fuzzy, phonetic, and synonym searching, users can tailor their queries to match the needs of any investigation.

In the next article in this series, we will look at various ways in which users can work with search results including creating reports to conduct contextual review and creating witness files.

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[1] The resulting number of hits and files was based on a search that did not utilize the synonym and related words search features.  Utilizing those features would have yielded 8 files and 34 hits.