Query Temporality Analysis for Search Result Ranking
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Solution Overview
Problem
Current information retrieval systems lack the ability to effectively filter and rank search results based on the trustworthiness and influence of sources, leading to unreliable decision-making due to the absence of objective measures for evaluating the reputation and influence of information providers, and fail to consider the temporality of queries in search results.
Innovation Solution
A system and method that utilize a citation graph to evaluate the influence of sources and objects, incorporating temporality analysis of queries to categorize intent and select relevant search results, thereby enhancing the ranking and filtering of information based on the reputation and recency of citations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional search engines are used to retrieve information, then a large quantity of data can be obtained, but the trustworthiness and reliability of the information sources cannot be evaluated
Solution Approach 1:
The patent introduces an intermediary influence evaluation engine that acts as a mediator between the search engine and search results. This engine calculates influence scores based on citation graphs and temporal analysis, providing an objective measure of source reliability without limiting the quantity of retrieved information.
Solution Approach 2:
The patent replaces subjective human judgment of source reliability with an automated computational system that uses citation graphs and temporal analysis to objectively evaluate and rank information sources based on their influence scores.
2Measurement precision
If more information sources are consulted to make informed decisions, then decision accuracy may improve, but the time required for information gathering increases
Solution Approach 1:
The patent performs preliminary evaluation of information sources by pre-calculating influence scores based on citation graphs and temporal characteristics. This allows the system to quickly filter and rank sources during search operations without requiring users to manually evaluate each source, thus maintaining decision accuracy while reducing time consumption.
3Reliability
If search results are filtered based on source influence scores, then the reliability of results improves, but the complexity of the search system increases
Solution Approach 1:
The patent segments the search system into distinct functional modules: a citation graph construction module, an influence evaluation engine, and a result ranking module. This segmentation allows each component to perform its specific function independently, making the overall complex system more manageable and maintainable while achieving reliable result filtering.
4Measurement precision
If temporal analysis is incorporated into query evaluation, then the relevance of search results to current intent improves, but the computational requirements increase
Solution Approach 1:
The patent incorporates temporal parameters into the influence score calculation by analyzing the recency and time-based patterns of citations. This allows the system to adaptively adjust the weight of different citation factors based on temporal characteristics, improving query intent matching while managing computational resources through parameter-based control.
Data Source
AI summary
A new approach is proposed that contemplates systems and methods to determine temporality of a query in order to generate a search result including a list of objects that are not only based on matching of the objects to the query but also based on temporality analysis of the query. Here, the temporality of the query can be defined as the distribution over time of the objects matching the query, i.e., the chronology histogram of the query. Such distribution can be analyzed to provide a classification of the intent of the query. Classification of the intent of the query can result either in discrete classification of the query into categories, or in continuous classification of the query which may be a scalar or vector value resulting from transformations of the chronology histogram.