Fey revolutionizes the interaction mode of traditional financial data queries by introducing Natural Language Processing (NLP) technology. This feature allows investors to retrieve specialized financial information directly using everyday language, such as typing in "Apple's latest earnings report" to quickly access relevant data.
The realization of this technology relies on three core technology layers: first, a semantic understanding engine that accurately parses user query intent; second, a knowledge graph system that establishes more than 5 million financial entity relationships; and finally, an intelligent sorting algorithm that ensures that the most relevant information is displayed first.
Practical cases show that using natural language search saves 75% operation time than traditional code query, and the accuracy rate reaches 92%. This function is especially suitable for the following scenarios: quickly obtaining the impact assessment of a specific event, comparing key indicators of multiple companies, retrieving the reasons for fluctuations in the historical market, etc.
As technology iterates, the feature is gradually supporting more complex long-sentence queries, and voice interaction capabilities will be integrated in the future. This human-centered design concept represents an important evolutionary direction for fintech tools.
This answer comes from the articleFey: Financial market research tools, intelligent assistants to enhance investment decisionsThe
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