Case Study .com Business

Introduction

For web portals it becomes increasingly critical to present information in a smart way and to guide the user instantly to the information he is looking for. The challenges are:

• Associative, smart and pro-active landing pages
• Intelligent next generation search
• Recommendation engines
• Usage of social and location based context

Case Study

In this application a web-portal allows art collectors to find information about artists, artworks, galleries, art fairs, and art auctions and so forth from a vast database. The main instruments to achieve this are landing pages and the search function, which uses a conventional search mechanism (such as Google). For example, if the customer wants to find out about the price of a particular artwork, he can type in the title of the artwork and click on search. The system then searches through the database to display matching results on the screen. The search results might include not only the artwork the customer is looking for but those other than artworks such as art fairs that include the keyword specified. This is because their current search solution cannot differentiate between artworks and art fairs; the system simply picks up anything with the keyword.

However, with SBSGRID artworks and art fairs can be recognized distinctively. In the case of the example above, the system will search for artworks only, excluding anything other than artworks even if it includes the keyword specified. SBSGRID therefore allows the user to find information with much greater precision and in less time.

Moreover, with the SBSGRID the user can look for information by specifying multiple categories and conditions. For example, the customer wants to find out if there are any art fairs in a specific week in New York that display some of the artworks of Andy Warhol. In their current system, the information cannot be found by typing in the keywords (although the information exists in the database). With SBSGRID, however, the information can be found easily with just one step by combining the three categories artist (Andy Warhol), location (New York) and art fair with the keyword say "week 24". This works because SBSGRID links data automatically based on meaning. The system searches through the "network of data" (with all its relationships) and finds the information that matches all entered semantic keywords. This is possible because the system recognizes different entities and its properties semantically (in its context) and does not just rely on the "text" entered.