Topic-Based Community Index Generation for Complex Network Search
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Solution Overview
Problem
Existing search technologies are limited in effectively and efficiently searching for communities within complex networks, as they fail to consider the diversity of topics and hierarchical relationships between nodes, leading to inaccurate and time-consuming query processing.
Innovation Solution
A topic-based community index generation apparatus and method that classifies communities into groups based on topics, generates a community index describing hierarchical structures, information about community groups, and relationships between them, using a seed node selection, neighboring node detection, community network creation, and topic determination to create a structured community index for efficient searching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing search technology is used to search for communities in complex networks, then the search process is simple, but the search accuracy and effectiveness deteriorate
Solution Approach 1:
The patent segments the complex network search problem into multiple components: community detection module, topic modeling module, and hierarchical indexing module. Each module handles a specific aspect of the search process, improving accuracy while managing complexity through modular design. The community detection module identifies tightly-knit groups, the topic modeling module extracts semantic meanings, and the indexing module organizes results hierarchically.
Solution Approach 2:
The patent introduces a hierarchical dimension to the search system by organizing communities into parent-child relationships based on topic categories. This creates a multi-level index structure where broad topic categories contain sub-categories, which in turn contain specific communities. This dimensional organization transforms the flat search space into a hierarchical structure, improving search accuracy through contextual filtering.
2Productivity
If existing search technology is used for community search, then the system structure is simple, but the search time increases
Solution Approach 1:
The patent performs preliminary actions by pre-detecting communities, pre-modeling topics, and pre-building hierarchical indexes before actual search queries are executed. The community detection and topic modeling are performed in advance on the entire network, creating a ready-to-use index structure. This preliminary processing transforms the raw network data into an optimized search structure, dramatically reducing query processing time for subsequent searches.
Solution Approach 2:
The patent creates a simplified copy or representation of the complex network structure in the form of a hierarchical index. Instead of searching the entire original network for each query, the system searches the pre-built index structure which mirrors the network's community organization. This copied index structure contains essential information about community relationships and topics, enabling fast retrieval without processing the full network complexity during queries.
3Measurement precision
If topic-based community classification is implemented, then search accuracy improves, but the system complexity increases
Solution Approach 1:
The patent segments the index structure into distinct hierarchical levels: topic categories, sub-categories, and communities. Each level serves a specific function in the classification process. The topic categories provide broad classification, sub-categories offer intermediate organization, and communities represent the finest granularity. This segmentation allows the system to manage complexity by breaking down the classification task into manageable, hierarchical components rather than attempting a single-level classification of all communities.
4Productivity
If hierarchical community indexing is implemented, then search efficiency improves, but the device complexity increases
Solution Approach 1:
The patent creates a universal hierarchical index structure that serves multiple functions simultaneously: it organizes communities by topic, enables fast search queries, supports navigation through parent-child relationships, and provides contextual information for result filtering. This single index structure performs what would otherwise require multiple separate systems, improving search efficiency while managing complexity through multi-functionality. The index can be queried at different levels depending on the search needs, making it adaptable to various query types.
Data Source
AI summary
A topic-based community index generation apparatus and method and a topic-based community searching apparatus and method are described. The topic-based community index generation apparatus generates a community index based on a topic that is shared by nodes included in a same community and is differentiated from topics of other communities. The topic-based community index generation apparatus and method effectively search for a desired community in a vast and complex network. In addition, the topic-based community searching apparatus and method effectively search for the desired community based on the topic that is shared by nodes included in the same community and is differentiated from topics of other communities.