A contextual border is a boundary of meaning — the invisible line that separates one knowledge domain from another. In NLP, this often shows up in topic segmentation tasks. In SEO, it parallels topical borders, which define the scope of ...

At its core, conversational search transforms information retrieval into a multi-turn dialogue rather than a one-off query-response. Instead of reformulating the same keywords, users can: Ask naturally: “Who is the CEO of Tesla?” Follow up: “How old is he?” Clarify: ...

CALM is a decoding strategy that adapts computation based on token difficulty. Instead of forcing every token to pass through the full stack of layers, CALM introduces confidence-based checkpoints. If the model is confident early, it stops processing deeper layers. ...

LaMDA (Language Model for Dialogue Applications) is a Transformer-based model developed by Google, trained on over 1.56 trillion words of dialogue and web text. At its peak, it scaled to 137 billion parameters, making it one of the most extensive ...

REALM is a retrieval-augmented Transformer architecture that bridges the gap between traditional language models and information retrieval systems. It combines three coordinated components: Retriever – searches a large external corpus (e.g., Wikipedia) for evidence passages. Knowledge-Augmented Encoder – reads both ...

PEGASUS is a Transformer-based sequence-to-sequence model designed specifically for abstractive summarization. Instead of training on generic text-prediction tasks, PEGASUS learns through a unique approach called Gap-Sentence Generation (GSG) — predicting the most important sentences that were deliberately removed from a ...

Golden Embeddings are multi-dimensional vector representations that combine semantic similarity, entity relationships, user intent, trust signals, and freshness thresholds. Unlike traditional embeddings, they aim to reduce semantic friction by aligning queries, content, and entities through credibility and context — delivering ...

Query breadth describes how many plausible subtopics, categories, and SERP formats a query can legitimately trigger. The broader the query, the higher the ambiguity and the greater the need for refinement. Broad example: “laptops” → brands, use-cases, prices, OS, reviews, ...

A Query Rewrite is the automatic transformation of a user’s query into a modified or alternative form to improve relevance, recall, or precision in search results. Example: “cheap hotel NY” → rewritten to “affordable hotels in New York City”. Example: ...

A Categorical Query is a user search input that explicitly or implicitly references a category, such as a product type, topical domain, or knowledge class. Example: “best DSLR cameras 2025” → category = DSLR cameras. Example: “lawyer in Karachi” → ...