Topic-Directed Search Using Coarse-Grained Topic Models
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Solution Overview
Problem
Conventional Web search engines struggle with providing focused and topically organized search results due to the lack of effective topical organization and the need for users to input minimal search queries, often resulting in disorganized and ambiguous results.
Innovation Solution
A computer-implemented system and method for topic-directed search that maintains a corpus of digital information with pre-computed coarse-grained topic models, allowing users to select topically related sub-indexes and topics based on search queries, enabling fast and practical topical search by matching search terms against characteristic words and scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional Web search engines use minimal search queries (one or two words), then user input effort is reduced, but search result precision and topical organization deteriorate
Solution Approach 1:
The system performs preliminary action by pre-computing and maintaining a comprehensive topical index with hierarchical categories and representative terms before user queries are received. This pre-organized structure enables the system to automatically interpret minimal queries and retrieve precise results without requiring extensive user input to specify search criteria.
Solution Approach 2:
The patent introduces an intermediary mechanism - a topical index with hierarchical categories and representative terms - that mediates between minimal user queries and comprehensive search results. This intermediary structure translates simple user input into precise topic-specific searches, resolving the contradiction between ease of operation and result precision.
2Quantity of substance
If Web search engines return information in disorganized jumble, then all search results are returned, but information assimilation and query formulation become difficult
Solution Approach 1:
The system segments search results by organizing them according to a hierarchical topical index structure. Results are divided into relevant categories and subcategories, presenting information in an organized manner that facilitates user assimilation while maintaining comprehensive coverage of all search results.
Solution Approach 2:
The patent applies preliminary action by pre-organizing the entire corpus of web information into a hierarchical topical index before search queries are received. This pre-segmented structure enables the system to automatically organize search results according to user interests without requiring post-processing or manual categorization.
3Adaptability or versatility
If Web search engines apply clustering techniques to channel search results, then popular themes are highlighted, but topically intermixed sets of articles remain
Solution Approach 1:
The system segments the topical organization into multiple hierarchical levels (categories, subcategories, representative terms) that work together to provide both broad theme-based organization and precise topic-specific classification. This multi-level segmentation resolves the contradiction by maintaining versatility while improving precision.
Solution Approach 2:
The patent adds another dimension to topic organization by introducing a hierarchical structure with multiple levels of categorization. This dimensional expansion allows the system to organize results both by broad themes and by specific topics simultaneously, resolving the contradiction between versatility and precision.
Data Source
AI summary
A system and method for providing a topic-directed search is provided, which advantageously harnesses user-provided topical indexes and an ability to characterize indexes according to how articles fall under their topical organizations. A corpus of articles and an index that includes topics from the articles is maintained. For each topic, a coarse-grained topic model is built, which includes the characteristic words included in the articles relating to the topic and scores assigned to the characteristic words. A search query is executed against the index. The topics that match the search terms are chosen by their scores. The topics that match the coarse-grained topic models and the articles corresponding to the search query are presented. In contrast to conventional search engines, search results are organized according to topic and search results can be offered across multiple indexes, where part of returned results are selected from most-relevant indexes with their most-relevant topics.