Google llc (20240289407). SEARCH WITH STATEFUL CHAT simplified abstract
Contents
SEARCH WITH STATEFUL CHAT
Organization Name
Inventor(s)
Mahsan Rofouei of Menlo Park CA (US)
Anand Shukla of Palo Alto CA (US)
Qing Wei of Mountain View CA (US)
Chi Tang of Mountain View CA (US)
Ryan Brown of San Diego CA (US)
Enrique Piqueras of San Jose CA (US)
SEARCH WITH STATEFUL CHAT - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240289407 titled 'SEARCH WITH STATEFUL CHAT
The abstract describes implementations for augmenting a traditional search session with a stateful chat, referred to as a "generative companion," to enhance interactive searching.
- A query is received from a user-operated client device, and contextual information related to the user or device is retrieved.
- A generative model processes data from the query and contextual information to generate output.
- Synthetic queries are created using the generative model output, and search result documents are selected.
- State data including the query, contextual information, synthetic queries, and search result documents is processed to classify the query.
- Downstream generative models are selected based on the classification to generate additional outputs.
Key Features and Innovation: - Integration of a generative companion to enhance traditional search sessions. - Utilization of generative models to process data and generate synthetic queries. - Classification of queries to select appropriate generative models for further output generation.
Potential Applications: - Improving user experience in search sessions by providing interactive chat capabilities. - Enhancing search result relevance through the use of generative models. - Personalizing search sessions based on contextual information.
Problems Solved: - Lack of interactivity in traditional search sessions. - Difficulty in generating relevant search queries based on user context. - Limited personalization options in search engines.
Benefits: - Increased user engagement and satisfaction. - More relevant search results tailored to user preferences. - Enhanced user experience through interactive chat features.
Commercial Applications: Title: "Enhancing Search Sessions with Generative Companions" Potential commercial uses include: - Integration into search engines to improve user engagement. - Implementation in e-commerce platforms for personalized product recommendations. - Adoption in customer service chatbots for more interactive interactions.
Prior Art: Further research can be conducted in the fields of natural language processing, chatbot technology, and search engine optimization to explore related technologies and advancements in generative models for search enhancement.
Frequently Updated Research: Stay updated on advancements in generative models, natural language processing, and user interaction technologies to enhance the capabilities of generative companions in search sessions.
Questions about Generative Companions: 1. How do generative companions differ from traditional chatbots in search sessions? Generative companions utilize generative models to process data and generate synthetic queries, enhancing interactivity in search sessions compared to rule-based chatbots.
2. What are the potential privacy implications of using generative companions in search sessions? Generative companions may raise concerns about data privacy and security, as they process user queries and contextual information to generate personalized search results.
Original Abstract Submitted
implementations are described herein for augmenting a traditional search session with stateful chat—via what will be referred to as a “generative companion”—to facilitate more interactive searching. in various implementations, a query may be received, e.g., from a client device operated by a user. contextual information associated with the user or the client device may be retrieved. generative model (gm) output may be generated based on processing, using a generative model, data indicative of the query and the contextual information. synthetic queries may be generated using the gm output, and search result documents (srds) may be selected. state data indicative of: the query, contextual information, one or more of the synthetic queries, and the set of search result documents, may be processed to identify a classification of the query. based on the classification downstream gm(s) may be selected and used to generate one or more additional gm outputs.
