Web search became part of our life. We don’t search anymore, we "google" everything . The visible simplicity of Google created a feeling that magic of search can transform and simplify any software product behavior. CAD, PLM and other enterprise software companies liked the idea as well. Search is certainly getting into mainstream. Open source search libraries such as Lucene and Solr created environment for easy implementation and distribution of search products across multiple software solutions.
At the same time, not every search solution can lead to simplicity. So called "laundry list" of results can be very disappointing for customers and lead to many questions about results relevance. Data matters and data can be nasty. Especially when it comes to complex engineering design, and enterprise data management solutions. To index data located in enterprise software packages can be a tricky problem.
Even web is not a search paradise these days. Google is still web search king. Even so, the relevance of some Google results is questionable. The complexity of Web search multiplied by social networks, mobile, combined with commercial interests of web giants created complexity that can be compared to the complexity of enterprise software. In parallel, there is a clear trend is enterprise software to adopt successful ideas of social software and social collaboration.
Recent Mashable article Yahoo’s New Long Game: Contextual Search puts some lights on the innovation and possible ways to solve problem of relevance in web search results. This is my favorite passage:
When I look at things like contextual search, I get really excited," Mayer said at the conference. Contextual search seeks to take in a variety of factors aside from a simple input to generate results that are tailored to a person’s time, place and patterns. For instance, a normal search for sushi might turn up a Wikipedia page or various websites about sushi. If one were to look up sushi from a phone through a contextualized mobile search, it could conceivably return nearby sushi restaurants with review, advertisements and coupons. The reason for Mayer to get excited is twofold: Nobody has yet mastered contextual search and it has the possibility of generating a ton of revenue.
Yahoo contextual search made me think about potential of such type of advanced search option for engineers. The specifics of engineering environment characterized by number of data dependencies, connected information and complexity to calculate the relevance search results. Engineering data can generate large volume of matches that hardly can be filtered based on simple filtering mechanisms. Think about document numbers, material names, design element names. Search for "shaft", "tube" and "aluminum" can generate thousands of results that hardly can be distinguished, sorted and ordered.
This is a place where I think "contextual search" does fit in a perfect way. What can be used a context for search (query) mechanism? Actually, quite many elements of easy available data can be re-used – date, time, organization, project name, team, location, previously used assemblies, etc. Some of these elements can be captured from the environment (computer, browser, application) and some of them can be captured from directly from users via specific user interface (capturing semantic). Result – significant decrease in the number of search results and better relevance.
What is my conclusion? Search is not simple. Even Google simplicity is questionable when it comes to the reality of engineering and enterprise data. New algorithms and additional data analysis must be applied in order to improve the relevance of results. Contextual search is not completely new idea, but it can become the next big deal in improving of search and overall user experience. Just my thoughts…