International business machines corporation (20240095270). CACHING OF TEXT ANALYTICS BASED ON TOPIC DEMAND AND MEMORY CONSTRAINTS simplified abstract
Contents
- 1 CACHING OF TEXT ANALYTICS BASED ON TOPIC DEMAND AND MEMORY CONSTRAINTS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 CACHING OF TEXT ANALYTICS BASED ON TOPIC DEMAND AND MEMORY CONSTRAINTS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
CACHING OF TEXT ANALYTICS BASED ON TOPIC DEMAND AND MEMORY CONSTRAINTS
Organization Name
international business machines corporation
Inventor(s)
Gandhi Sivakumar of Bentleigh (AU)
Smitkumar Narotambhai Marvaniya of BANGALORE (IN)
Vijay Ekambaram of Chennai (IN)
Luke Peter Macura of Lucas (AU)
CACHING OF TEXT ANALYTICS BASED ON TOPIC DEMAND AND MEMORY CONSTRAINTS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240095270 titled 'CACHING OF TEXT ANALYTICS BASED ON TOPIC DEMAND AND MEMORY CONSTRAINTS
Simplified Explanation
The abstract describes a patent application that involves analyzing user queries to identify a topic, mapping it to a topic cluster in a text database, generating query demand data, and caching the text of the topic cluster based on available memory space.
- Analyzing user queries to identify a query topic
- Mapping the query topic to a topic cluster in a hierarchical text database model
- Generating query demand data based on user queries
- Identifying the topic cluster as a topic-cache candidate
- Comparing memory requirements for storing text with available cache memory
- Caching the text of the topic cluster if sufficient memory space is available
Potential Applications
This technology could be applied in search engines, content recommendation systems, and information retrieval systems.
Problems Solved
This technology helps in efficiently storing and retrieving text data based on user queries, improving system performance and user experience.
Benefits
The technology optimizes memory usage, enhances search results, and speeds up information retrieval processes.
Potential Commercial Applications
Commercial applications include search engine optimization tools, content management systems, and online advertising platforms.
Possible Prior Art
One possible prior art could be the use of caching mechanisms in information retrieval systems to improve performance and user experience.
Unanswered Questions
How does this technology handle user privacy and data security?
The article does not address how user data is handled and protected within the system.
What are the scalability limitations of this technology?
The article does not mention the scalability limitations of the technology and how it performs with a large volume of user queries.
Original Abstract Submitted
an embodiment includes analyzing text content of a user query to identify via natural language processing (nlp) a query topic. the embodiment maps the query topic to a topic cluster at a node of a hierarchical model of a text database. the embodiment generates query demand data indicative of demand for the topic cluster based on user queries. the embodiment identifies the topic cluster as a topic-cache candidate based on the query demand data. the embodiment compares an amount of memory required for storing text associated with the first topic cluster to available cache memory. the embodiment caches the text of the topic cluster candidate upon determining that there is sufficient available cache memory space.
