Search engines are tools that allow searching for sites, documents, files, list items, content, answers to questions and other digital information.
They allow specifying the scope or domain of the search, whether to search on text or metadata, and how results should be presented.
Enterprise search is making content from multiple enterprise-type sources, such as databases and intranets, searchable to a employees and other authorized users through a single, ubiquitous search engine.
For many users, search is the primary tool they wish to use to find information, answer questions, and learn about a topic. The success of Google Web Search on the Internet has resulted in the widespread expectation that searching within an organization should work the same way. Users would like to enter just a few words into a search text box and be presented with a list of results that match exactly what they are seeking. Too many hits are not desired, nor are too few, nor are irrelevant ones.
There are significant differences between the quality of results returned by an Internet search and from enterprise search. Page ranking is typically done based on a large sample of links, which works well in the gigantic realm of the Internet, but not as well in the smaller confines of an intranet.
Users should be able to narrow or broaden the types of content, the domains or sites, and the range of metadata values to be included in the search. They should be able to search for text strings, metadata values, or content titles. Familiar syntax such as Boolean operators, quotation marks, and command words used by popular search engines such as Google should be offered. The ability to refine searches, use advanced search functions, and remember previous searches should be provided.
A typical text search should allow entering a text string and finding content that contains that string or similar text. For example, entering “electric battery” in the search text box should return all content containing that string.
Content title search should allow finding files whose title contains a specific text string. For example, searching for “+Honda +Civic +engine” in the content title field should return only documents or photos about Honda Civic engines.
Look for opportunities to integrate existing enterprise search with specialized search within the KM environment. If there is content that can’t be crawled by enterprise search, consider implementing a federated search or a single search interface to multiple search engines.
If your enterprise search offers a best bet feature for common searches, take advantage of that by defining best bets for the most frequently searched for topics. If not, consider implementing this feature.
Reviewing the logs of your enterprise search will allow you to get insight into what users are looking for. You can use this information to supply the most frequently searched for terms in your user interface. You can also use it to improve navigation, offer best bets, and update metadata definitions. Knowledge assistants can monitor user searches to better prepare for user requests.
Most intranet, portal, and repository tools include search engines as part of the standard offering. If these don’t provide adequate functionality, consider adding a commercial search tool to strengthen the existing environment, and adding cognitive search capability.
For more information on enterprise search, see the following.
- The Forrester Wave™: Cognitive Search, Q3 2021
- Gartner Magic Quadrant for Insight Engines, 2021
- KMWorld 2021 Sourcebook and Buyers’ Guide
Lucidea Blog Posts
Please enjoy Stan’s additional blog posts offering advice and insights drawn from many years as a KM practitioner. You may also want to download a copy of his book, Proven Practices for Implementing a Knowledge Management Program, from Lucidea Press. And learn about Lucidea’s Inmagic Presto and SydneyEnterprise with KM capabilities to support successful knowledge curation and sharing.
Knowledge capture includes making entries into databases; examples of this information include personal profiles, repositories, and knowledge bases.
Content captured as part of a KM program includes documents, communications of various types, and training. Details each type, how to capture.
Knowledge capture includes collecting documents, presentations, spreadsheets, records, etc. that can be used for innovation, reuse, and learning.
KM thought leaders; Mary Lee Kennedy is the Executive Director of ARL and led design and implementation of KM strategies at Microsoft