Many business applications need to allow users quickly find documents or data based on a text query.
For example, a Human Resources department may need to quickly search through the CV of candidates to find specific skills or experience. Or maybe a Legal department needs to find contracts containing particular clauses or conditions. Or a Customer Service department may need to find a knowledge article while having the client on the phone.
There are many different methods how to do this. It may be a simple exact match between the search query and records in the database. Or it may be something more advanced that forgives typos, allows search by different word forms, and does much more. Also, some methods allow searching large volumes of data at an incredible speed, similar to your user experience with Google.
Finally, the most advanced type of text search goes beyond keyword matching and finds documents based on the meaning of the query.
And many of these methods can be applied in your business applications at an affordable cost.
So, let’s take a closer look at each of these techniques.
Simple Keyword Search
This is the simplest search technique that finds exact matches of words or phrases in your database and returns results that correspond only to them.
For example, if the user searches for “project management,” the system will look for documents that contain the exact phrase. However, it will not find similar words like “managing a project.” Also, suppose a record in the database has a typo, for example, “project managament.” In that case, it will not appear in search results.
Why is this search technique the most popular? First, it comes out of the box in most databases. Also, you do not need anything else to implement this method. So it is easy to develop and maintain.
However, you may use more sophisticated methods if the limitations are not acceptable.
Fuzzy search is built to solve the problem of typos and different word forms. It allows some degree of “fuzziness” in search. It finds results even if there are slight misspellings in them. Beyond this, if the query contains a singular form of a noun, documents that have it in the plural form will also appear.
Similar to the simple keyword search, it may work directly on the database where you keep your data. Even though it is not a common feature of databases, it is possible to build it using any popular programming language.
However, this will work well only on relatively small datasets. If it is not your case, consider the following method.
If you have a repository of long texts or if your database contains many records, a different solution for a full-text search may be what you need. Again, the architecture will be different compared to the first two techniques. In this case, you must separate search functionality from the primary database, creating a Search Index.
If done correctly, a full-text search may be lightning fast, even on massive volumes of data. Also, it may allow many advanced techniques, including fuzzy search discussed above, proximity search, and others.
Some databases offer this extended functionality as part of their suite. Also, there are many solutions designed specifically for this purpose. And some of them do not require you to buy expensive licenses as they are free to use, for example, Elastic Search and Apache Solr.
All the methods explained above are called “lexical search” as they all rely on matching words in the query and the searchable data. Alternatively, semantic search is something different and, in some cases, more powerful.
It uses Artificial Intelligence (natural language techniques) to understand the meaning of text or query instead of just finding exact matches.
For example, suppose you search for “project management” using a semantic search. In that case, it will look for exact matches and understand that the query is related to words like “planning,” “scheduling,” and so on.
And considering the advancements in this field, this kind of search has become very affordable, even for small and medium companies. Different solutions may be used to empower your applications with semantic search. Some of them are open-source, and they may be used for free. Others are offered as ready-to-use cloud solutions.
There are many ways you can implement search within your application or database. Selecting the best one will depend on what you need it for.
A simple keyword search enhanced with fuzzy logic could be the best if you have primarily simple and obvious queries and a small dataset. On the other hand, the full-text search with a separate search index could be the answer if you have more extensive searchable databases. And if you are searching for meaning or related concepts, semantic search is your tool of choice.
Regardless of the technique, improving the search functionality of your application or database is always a good idea. It will help your users quickly find what they need making them more efficient.
This article was originally posted by us on Meduim.