We humans by nature don’t like long lists of things. Our brains get easily overwhelmed and, as cognitive misers, we prefer fewer options, shorter sentences and paragraphs, etc. Psychological research shows that humans can only parse seven plus or minus two things at a time—words in a sentence, sentences in a paragraph, menu items, etc. This proves true when you go to your neighborhood Mexican restaurant and there are literally pages and pages to the menu loaded with more choices than you can possibly consume and decision making becomes a stressful event. Business 2 Community brought this news to us in their article, “Managers of large sites must balance search AI with navigation IA“.

It is important to remember this overwhelming feeling when it comes to building internal search engines. Users expect a good search experience and they likely don’t know what is required from them to achieve that. The responsibility lies on the designer. If they try to build a search engine that just matches query strings to the frequency, density or prominence of keywords in content, it will likely fail. What you need is semantic search, which doesn’t just match queries to keyword strings, but matches content to the the searcher’s intent implicit in the query.

Semantic search engines use natural language processing and machine learning to find the content most relevant to a searcher’s intent.

Melody K. Smith

Sponsored by Access Innovations, the world leader in thesaurus, ontology, and taxonomy creation and metadata application.