# OLGAVis: On-Line Graph Analysis and Visualization for Bibliographic Information Network
## 3 Design of Bibliographic Data Analysis System
### Operations on Bibliographic Information Network
#### 3.4.2 BIN Aggregation Type of Operations  
**Operation 4**. **AggregateBIN**  
- Syntax : \(AggregateBIN(Function,Target,GroupBy)\)  
- Argument : Aggregate function, target node, group-by nodes  
The AggregateBIN operator applies a function to create a summarized aggregation network. The aggregate function to be used, the node type to be aggregated, and a type of grouping node that is the viewpoint of the aggregation are selected as input. Query Example 5 shows an example of creating a network by counting the number of papers published in each event for the authors who have written papers that were published in conferences. For example, for \"A1\" author, who has published two papers in \"V1\" conference, the \"V1\" Venue node and the \"A1\" Author node are directly connected, and \"2\" of the number of papers aggregated by the edge label are displayed.  
**Example 5**.: _AggregateBIN(Function=Count, Target=Paper, GroupBy=(Venue, Author))._  
**Operation 4**. **FindNode_TopDegree**  
- Syntax : \(FindNode\_TopDegree(CurrentBIN,k)\)  
- Argument : currentBIN, top-k  
The FindNode_TopDegree operation is an operation that retrieves the node with the largest number of edges. The author collaboration relationship network created, as shown in Example 6, enables querying the top three authors who have extensively participated in collaboration with other authors. The aggregated information network was created by calculating the number of edges for each node, and the value of the operator's input parameter k was set to 3.  
**Example 6**.: _FindNode_TopDegree(CurrentBIN, 3)._  
**Operation 5**. **FindCommunityHub**  
- Syntax : \(FindCommunityHub(CommunityBIN,Centrality\_Measure))  
- Argument : communityBIN, Centrality measure function to calculate hub  
Among the operators that were proposed in this paper, operators, such as GetConnotation, can be used to create a type of community. The FindCommunityHub operator can be used to search for the central or influential node of the community for the community network that was created as a result of the operation. The most fundamental and well-known indicators among the various indicators used to find an important node in the nodes constituting a network are Degree Centrality, Closeness Centrality, and Betweenness Centrality. The FindCommunityHub operator takes one of these indicators as a user input parameter, calculates the influential node, and creates the resulting network. Example 7 analyzes authors with high influence on the author collaboration relationship network created in Query Example 4 to create an information network. Among the indicators for calculating authors of high importance, the authors with a high influence in the author network were searched based on the closeness centrality, which measures the node with the shortest path to all other nodes.  
**Example 7**.: _FindCommunityHub(CommunityBIN, Centrality_Measure=closeness)._  
**Operation 6**.: **Trim**  
- Syntax : \(\mathit{Trim}(CurrentBIN,condition)\)  
- Argument : currentBIN, trimming condition