Inverted Index Search Using Click-Through Special Postings
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Solution Overview
Problem
Conventional search engines fail to include potentially relevant data items in search results due to imprecise search queries, as they do not utilize click-through data effectively during the initial search stage, leading to missed opportunities in presenting relevant results to users.
Innovation Solution
The method involves using click-through data to create 'special' postings in the inverted index, indicating that a data item has been clicked on in previous queries, even if it lacks specific search terms, allowing these items to be included in search results based on their implicit relevance, and adjusting the quorum rule to account for both standard and click-through postings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional search engines only include data items containing all specified search terms in the inverted index, then search precision is maintained, but search recall deteriorates (potentially relevant items are missed)
Solution Approach 1:
The system performs preliminary actions by analyzing click-through data from previous queries to identify data items that users actually selected, even when those items didn't contain all search terms. This pre-computed relevance information is stored and used to supplement the traditional inverted index, allowing the system to recall relevant items that would otherwise be missed by strict term-matching.
Solution Approach 2:
The system implements feedback by utilizing click-through data from user interactions with search results. This feedback loop captures implicit user preferences and relevance signals, which are then integrated into the search indexing mechanism. The feedback enables the system to learn from actual user behavior and improve both recall and precision over time.
2Quantity of substance
If the inverted index is expanded to include all potentially relevant data items, then search recall improves, but device complexity increases
Solution Approach 1:
The search index is segmented into two distinct components: the traditional inverted index based on explicit term matching, and a click-through based index derived from user interaction data. This segmentation allows each component to serve its specific purpose without overwhelming the system with a single monolithic structure, managing complexity while improving recall.
Solution Approach 2:
Click-through data acts as an intermediary that bridges the gap between explicit search terms and implicit document relevance. Rather than directly expanding the traditional inverted index with all possible relevant items, the system uses click-through signals as a mediator to identify and prioritize potentially relevant items, reducing the need for brute-force index expansion.
3Measurement precision
If click-through data is utilized during the initial search stage, then search relevance improves, but processing time increases
Solution Approach 1:
Click-through analysis and relevance scoring are performed as preliminary actions during the indexing phase, not during query processing. This pre-computation of relevance signals based on historical user behavior allows the search stage to quickly retrieve relevant items without performing complex real-time analysis, thus improving relevance while minimizing additional processing time.
Solution Approach 2:
The system dynamically adjusts the weight and influence of click-through data based on query characteristics and user profiles. Rather than uniformly applying click-through signals to all searches, the system adapts their usage to balance relevance improvement with processing efficiency, optimizing the trade-off between search quality and speed.
Data Source
AI summary
Method of searching an inverted index having a plurality of posting lists, comprising: receiving a search query to be searched including search terms; effecting a search of posting lists to yield search results, the posting lists associated with the search terms and including a plurality of a first type of postings being a reference to a data item actually containing the search term with which that posting list is associated, the search results including result items missing one of the search terms; sending the first search results; receiving an indication of a user-selected result item, the user-selected result item being the result item missing one of the search terms; effecting insertion, into the posting list associated with the missing one of the search terms in the user-selected result item, of a second-type of posting being a reference to the user-selected result item missing that search term.