Partial Query Prediction System for Online Dictionaries
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Solution Overview
Problem
Existing online dictionary services lack efficient methods for predicting and suggesting complete queries based on partial user input, particularly across languages, and do not effectively handle misspellings or provide personalized results.
Innovation Solution
A distributed system that processes partial search queries by mapping them to a chunk table and token table, using a prediction database and dictionary database to generate and rank predicted complete queries, which includes handling misspellings and personalization based on user query logs and language pair selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If online dictionary services require users to enter complete words or terms for translation, then translation accuracy is improved, but user operation time and convenience deteriorate
Solution Approach 1:
The system pre-computes and stores prediction results for partial queries in advance. When a user types a partial query, the system retrieves pre-computed predictions from the prediction database, eliminating the need for real-time computation and enabling fast suggestions before the user completes typing.
Solution Approach 2:
The system introduces a prediction interface as an intermediary between the user's partial input and the complete query submission. This prediction interface provides suggested completions that guide users toward accurate translations without requiring them to manually type the complete query, thus maintaining accuracy while reducing time.
2Ease of operation
If the system provides prediction suggestions for partial queries, then user convenience is improved, but system complexity increases
Solution Approach 1:
The system segments the query processing functionality into distinct modules: a prediction module that handles partial query suggestions, a translation module that processes complete queries, and separate database components (prediction database and dictionary database). This modular architecture manages complexity by dividing functions into independent, manageable units.
Solution Approach 2:
The prediction interface acts as an intermediary layer between the user and the complex translation system. It simplifies user interaction by providing guided completions while managing the complexity of query processing, database searches, and translation operations in the background without exposing this complexity to the user.
3Measurement precision
If the system uses comprehensive databases for query predictions, then prediction accuracy is improved, but data processing time increases
Solution Approach 1:
The system pre-computes prediction results for partial queries and stores them in advance in the prediction database. This preliminary computation eliminates the need for real-time analysis of the complete dictionary database when providing suggestions, enabling fast retrieval based on pre-processed data while maintaining high prediction accuracy.
Solution Approach 2:
The system segments the large dictionary database into a smaller, optimized prediction database that contains only the necessary prediction data for partial queries. This segmentation reduces the amount of data that needs to be processed in real-time while maintaining prediction accuracy by storing pre-computed results.
Data Source
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AI summary
In accordance with some embodiments, a server receives a partial search query from a client device that is located remotely from the server, and predicts from the partial search query a set of predicted complete queries relevant to the partial search query, where the predicted complete queries comprise previously submitted complete queries submitted by a community of users. The partial search query and the set of predicted complete queries are in the same language. In addition, the server obtains translations of at least a subset of the set of predicted complete queries, where the translations are in a different language from the set of predicted complete queries, and conveys both the set of predicted complete queries and the corresponding translations to the client device.