Enterprise Search

I’m Marin Smiljanić, the co-founder and CEO of Omnisearch, a startup building the next generation of B2B search engines with a focus on search audio and video. Omnisearch is particularly strong in the education vertical, where our search product reaches over 400,000 students and helps them navigate online course materials…

This week we feature articles from Gary Marcus and Daniel Tunkelang. News comes from Access Innovations, Brightspot, Super .AI, and Indico Data. We’ll be off next week, back the week after. Opinion / Analysis… Deep learning is hitting a wall There has always been a healthy skepticism that deep learning would take us to artificial general intelligence (AGI). But…

What are the development and trends in the knowledge management space? Dorian Selz, CEO and Co-Founder of Squirro, has been a guest on the Knowledge Cast podcast with Joe Hilger, COO of Enterprise Knowledge. One important transition that has taken place in the last 20 years is the move from search to insight. Supplementing search with context allows for bringing tailored information directly to the user, instead of the user poking in the dark.

Sentiment analysis is an essential ML technique to classify the emotions found within the unstructured text. Product reviews, customer surveys, employee feedback, chat messages, customer support tickets, call center audio files, and discussion boards contain free-form text which needs to be analyzed for sentiments. …

Originally posted 16-Dec-21 Search engines are tools that allow searching for sites, documents, files, list items, content, answers to questions and other digital information. They allow specifying the scope or domain of the search, whether to search on text or metadata, and how results should be presented. Enterprise search is…

Photo by Mateusz Wacławek This is part 3 of a 4-part blog post series on Vector vs. keyword search: War of the worlds vs. we come in peace Data structures and algorithms LSMT-IVF for Billion-Scale Approximate Nearest Neighbor Search Benchmarking Vector vs. keyword search 3: LSMT-IVF for Billion-Scale Approximate Nearest Neighbor Search While in the first part we concentrated on the more…

Photo by Mateusz Wacławek This is part 2 of a 4-part blog post series on Vector vs. keyword search: War of the worlds vs. we come in peace Data structures and algorithms LSMT-IVF for Billion-Scale Approximate Nearest Neighbor Search Benchmarking Vector vs. keyword search 2: Data structures and algorithms Now lets’s take a closer look at the inner workings…

Technology becomes more complex and faster changing, data become more massive, and competition denser by globalization. There are different approaches to cope with these challenges. One is to build your application based on available libraries and best practices. This high-level approach on top of existing building blocks allows you to…

The red panda may very well have all the info it needs. It is relaxed and content. For we humans, the search for information never ends. Imagine the scenario below: You are rushing to make an all-important presentation. You are almost there but missing critical competitive research data. You recall…