Unite.AI
NOVEMBER 27, 2024
Traditional business intelligence processes often involve time-consuming data collection, analysis, and interpretation, limiting an organization’s ability to act swiftly. Traditional customer segmentation methods are limited in scope, often categorizing customers into broad groups.
Marktechpost
MAY 7, 2024
As thousands of organizations leverage Business Intelligence (BI) for decision support, industry researchers have honed in on NL2BI, a scenario where natural language is transformed into BI queries. Existing NL2SQL methods primarily handle Single-Round Dialogue (SRD) queries and struggle with MRD scenarios.
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Unite.AI
AUGUST 11, 2024
With a range of affordable pricing plans, it caters to businesses of all sizes, from startups to large enterprises. It enables businesses to monitor brand mentions, track sentiment, and gain audience insights across various social networks and the web.
MARCH 13, 2025
The author, Matthew Barnett, uses a commercially available AI model (GPT-4o) to go through a US Department of Labor-sponsored database of over 19,000 job tasks and categorize each of them as doable remotely (writing code, sending emails) or not doable remotely (firefighting, bowling). A task, notably, is not the same as a job or occupation.
IBM Journey to AI blog
AUGUST 28, 2023
As it pertains to social media data, text mining algorithms (and by extension, text analysis) allow businesses to extract, analyze and interpret linguistic data from comments, posts, customer reviews and other text on social media platforms and leverage those data sources to improve products, services and processes. How does text mining work?
AWS Machine Learning Blog
FEBRUARY 25, 2025
As AIDAs interactions with humans proliferated, a pressing need emerged to establish a coherent system for categorizing these diverse exchanges. The main reason for this categorization was to develop distinct pipelines that could more effectively address various types of requests. values.tolist()) y_train = df_train['agent'].values.tolist()
AWS Machine Learning Blog
JUNE 25, 2024
Manually analyzing and categorizing large volumes of unstructured data, such as reviews, comments, and emails, is a time-consuming process prone to inconsistencies and subjectivity. We provide a prompt example for feedback categorization. Extracting valuable insights from customer feedback presents several significant challenges.
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