Posts Tagged ‘Findability’
Semantic Search Is Only as Smart as Its Governance
Semantic search promised more than traditional keyword search: an understanding of meaning, context and intent. Instead of matching exact words, it can connect a question with relevant information even when the language differs. But that intelligence depends on more than a fancy new model. It depends on well-governed data. MarTech brought this topic to our…
Read MoreData Quality Is Still the Foundation of Information Science
For information science professionals in higher education, data quality is hardly a new concern. Long before generative artificial intelligence (GenAI), machine learning and advanced analytics entered the conversation, the principle was simple: information systems can only be as trustworthy as the data they contain. This important topic came to us from IT Brief and their…
Read MoreSemantic Search and the Preservation of Scholarly Intent
For decades, academic publishing has focused on creating authoritative, peer-reviewed content designed to advance knowledge. Yet, as discovery increasingly depends on artificial intelligence (AI) and semantic search systems, a new challenge has emerged: ensuring that scholarly intent survives machine interpretation. Semantic search differs from traditional keyword search by attempting to understand meaning rather than simply…
Read MoreOntology: The Invisible Architecture Powering Findability in the Age of AI
In information science, ontology is one of those terms that sounds intimidating but quietly does some of the most important work behind the scenes. At its core, an ontology is a structured framework that defines the relationships between concepts within a domain. It goes beyond simple lists of terms or categories by mapping how ideas…
Read MoreRecords Retention in the Age of AI: Why Taxonomy Still Reigns Supreme
In a world increasingly shaped by artificial intelligence (AI), records retention has moved from back-office obligation to strategic necessity. AI systems thrive on data, but not just any data—relevant, accurate, well-structured data. Without intentional retention policies, organizations risk feeding their AI outdated, redundant or even harmful information, leading to flawed outputs and questionable decisions. This…
Read MoreEvolution in Search
Early search engines relied almost entirely on keywords, treating every query as a string of terms to be matched against web pages. Results were based on how often those words appeared and where they were placed. This approach worked for a time, but it assumed that users always knew the exact words to use and…
Read MoreSearch Is Not About Keywords Anymore
Search used to be pretty simple. You typed in a few words and the system looked for pages that repeated those words back to you. The more matches, the better the result. It worked well enough for a while, as long as you knew exactly what to type and spelled it correctly. The Scholarly Kitchen…
Read MoreFrom Keywords to Conversations: The Evolution of Search
Search used to be a fairly straightforward exchange between humans and machines. Early search engines focused almost entirely on keywords. If you typed in the right words and those words appeared frequently enough on a page, you were likely to find what you needed. It was efficient, but it assumed everyone knew the exact terms…
Read MoreFrom Keywords to Conversations
Search began as a simple transaction between people and machines. Early search engines relied almost entirely on keywords, treating every query as a string of terms to be matched against web pages. Results were based on how often those words appeared and where they were placed. This approach worked for a time, but it assumed…
Read MoreTaxonomies Provides Direction
Every second, information floods in from research papers, shopping sites, company server, etc. The real challenge isn’t getting access to it; it’s cutting through the noise to find exactly what you need, exactly when you need it. That’s where an unsung hero steps in: the taxonomy. Content Science Review brought this topic to us in…
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