Going back and forth between Object Search and Visual Data Browser

Fig.1. Linking between Object Search and Visual Data Browser

In NaverLab Semantic Movie Search, user goes back and forth between Object Search and Visual Data Browser. Search for the object of interest using Object Search and explore related information of the object using Visual Data Browser.

User initiates the search from Object Search and find the object of his/her interest with the keyword search. Then he/she expands the object to further explore. In order to expand the object there are two ways. One is to click the [expand + more] button (Refer to the arrow of No. 1 in Fig. 1). Another is to click the object itself and popup the property menus, then click one of the properties of the object. (Refer to the arrow of No. 2 in Fig. 1)

While browsing the data space, user decides to search for new object. He type in keywords in the search box and click the search button. (Refer to the arrow of No. 3 in Fig. 1) This brings him back to Object Search. Another method for coming back to Object Search is to click the object itself and popup the property menus, then click the small magnifier icon inside the thumbnail image. (Refer to the arrow of No. 4 in Fig. 1)

Keyword search and Object search

Fig. 1. Transforming the keyword query to the object query using the auto-completion

Keyword query is the most common query interface for text information. Especially in Web era the keyword query interface is ubiquitous for all kinds of searching. The keyword search is easy to use and very effective for searching the Web. Users got so accustomed to the keyword search. It would not be easy to develop a new query interface so as to replace the keyword query interface.

The keyword search is to match a keyword query to the text surrogate of the objects. In NaverLab Semantic Movie Search, a keyword query is transformed to the multiple object queries. This is because of the ambiguity of natural language.

On the other hand the object search is to match an object query directly to the objects. So the keyword-object mapping is not necessary. There are no ambiguities caused by natural language. But there are ambiguities caused by the structure of the RDF graph.

In NaverLab Semantic Movie Search, users use both the keyword query and the object query. The object query is used when the auto-completion is applied. (Fig. 1) After auto-completion, the keywords in the search box look like just plain strings but actually they are objects.

It is difficult for users to notice the difference between the keyword search and the object search. Let's see the difference with the query "avatar". Fig. 2 is the search result of the keyword query "avatar" and Fig. 3 is the search result of the object query after auto-completion.

Fig. 2. The search result of the keyword query "avatar"

Fig. 3. The search result of the object query "avatar" after auto-complection

From keywords to objects

Fig. 1. Three meanings of the query "Ben Hur"

In NaverLab Semantic Movie Search, user always initiates search from the keyword interface. This is for the disambiguation of the meaning of the keyword query. If the meaning of the query is ambiguous, in other words there are more than two meanings, all the search results of the possible meanings are displayed. Then user decide which meaning to further explore.

If there remains only one meaning after the disambiguation, it is possible to launch directly the visual data browser. But in NaverLab Semantic Movie Search, the keyword interface (Object Search) is chosen to launch anyway. This is just the problem of policy. We thought this way is more intuitive and usable for users to use.

Let's run the query "Ben Hur". There are three multiple meanings and three movies that have the same title "Ben Hur" are returned. (Fig. 1) Let's see another query that have only one meaning. The search result of "shawshank redemption" is in Fig. 2. Only one movie is returned but other expanded query results (director, leading actors, etc) follow after. This is just for user's convenience.

Fig. 2. In the case of single meaning, the results of the expanded queries are shown together for user's convenience