Entity Alias Extraction via Lexical Pattern Analysis
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Solution Overview
Problem
Conventional Internet search engines lack the ability to collect and link all possible aliases associated with an entity, leading to incomplete search results, as aliases and nicknames can vary quickly and are not efficiently extracted or linked.
Innovation Solution
A search system comprising a storage module, a search module, and an alias extracting module that uses lexical patterns to identify and extract aliases from database snippets, building a relationship table for efficient future searches, and an additional module for automatic extraction and updating of lexical patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional search engines use simple name-based searching, then the search process is fast and simple, but the search results are incomplete and miss aliases
Solution Approach 1:
The system performs preliminary actions by pre-collecting and storing aliases associated with entities in a database before search queries are executed. The alias extracting module proactively gathers aliases from various sources and builds an alias database in advance, so that when a search is performed, the system can immediately expand the search query to include all known aliases, thereby improving result completeness without adding complexity to the actual search process
Solution Approach 2:
The patent introduces an intermediary alias database that mediates between the simple name-based search input and the comprehensive search results. This intermediary layer contains pre-extracted aliases and acts as a bridge, allowing the system to maintain simple user-facing search interfaces while internally performing complex alias-based expansions to improve information retrieval completeness
2Reliability
If the system manually collects and maintains aliases, then the alias database is accurate, but the maintenance cost and time consumption are high
Solution Approach 1:
The system implements self-service by automatically extracting aliases from web pages and other sources using the alias extracting module. The module autonomously crawls, parses, and validates alias information without human intervention, and the database automatically updates itself. This self-maintaining mechanism ensures high reliability of the alias database while eliminating the time-consuming manual maintenance that would otherwise be required
Solution Approach 2:
The system incorporates feedback mechanisms where the alias extracting module continuously monitors and extracts new aliases from search results and web content, feeding this information back into the alias database. This automated feedback loop ensures the database remains accurate and up-to-date without manual intervention, maintaining high reliability while minimizing maintenance time through continuous automatic refinement
3Loss of information
If the system searches for all possible aliases, then the search coverage is complete, but the search time and computational resources increase
Solution Approach 1:
The system applies preliminary action by pre-processing and storing alias relationships in a structured database before searches are executed. During the search process, the system quickly retrieves relevant aliases from this pre-prepared database and expands the query accordingly, rather than performing complex alias resolution in real-time. This approach maintains complete search coverage while significantly reducing search time by avoiding computational overhead during the actual query execution
Solution Approach 2:
The patent segments the search process into distinct phases: alias retrieval from the pre-built database, query expansion with found aliases, and result aggregation. This segmentation allows the system to efficiently handle alias-based searching by separating the computationally intensive alias extraction (done beforehand) from the quick query execution phase, thereby maintaining comprehensive search coverage without proportionally increasing search time
Data Source
AI summary
A search system for collecting aliases associated with an entity name, includes a storage module configured to store at least one first lexical pattern, a search module coupled to the storage module and configured to obtain a plurality of first snippets from a database according to the entity name, and an alias extracting module coupled to the storage module and the search module separately and configured to, according to the entity name and the first lexical pattern, determine whether any first alias exists in the first snippets. If a first alias exists, the alias extracting module extracts it out and stores it in the storage module.