Information Retrieval

Information Retrieval (IR) is an important field of research in computer science. It is not only about building big search engines like Google or Bing. We can face IR systems when use an online store search, chat-bot or receive an automatic email with recommended online courses. IR is a hot…

Information Retrieval (IR) is the process of obtaining relevant resources from a collection of available resources against a given question or query. A query is basically a set of keywords used to search for a resource on any platform. You give a query to the IR system, and you are…

There are a lot of explanations elsewhere, here I’d like to share some example questions in an interview setting. Last week we joined the hype for ChatGPT. Following the same train of thought, let’s think more about informational retrieval and natural language understanding problems. What is Information Retrieval (IR)? How…

Many-a-times we wish to search for news relevant to our field of work, domain of expertise, or our organization in general. What do we do? We browse our favorite search engine, type a search query, and voila…results pop-up. Do we realize that the search engine at the back end processes…

TLDR — The key innovation which has allowed for huge advances in semantic search has primarily been improvements in training methodology. Naive approaches to contrastive learning don’t present a challenging enough problem to force models to learn interesting representations. Erroneously sampling false negative examples greatly hurts model performance. New techniques…

by Malvina Matlis & Marcos Calvo Lance Information retrieval (IR) systems are ubiquitous in our day to day. Maybe it’s settling bets by searching for the answer online, locating your favorite products on Amazon, finding any email in Outlook, or perhaps you’re just hungry and want to cook a delicious…

This post surveys recent techniques for semantic product search, especially neural network models. We introduce and classify a number of models, and describe the commonalities and differences in their characteristics such as model architecture, loss function, etc. We believe familiarity with the various choices of the building blocks in semantic…

Information retrieval (IR) technology is the core of all search engines and the first step of open-retrieval question answering (ORQA). In ORQA, since the correct context or document that contains the answer is not given, the QA system needs to first retrieve the candidate documents from a database such…

TLDR — Single vector embedding search model’s are efficient for search but they create an information bottleneck which limits performance. In this review we introduce a class of models which represent text using multiple embeddings such as ColBERT. The literature shows that these models are much better at domain transfer…