Best Practices for Intelligent Search

Sinequa provides an AI-powered search & analytics platform that enables organizations to become information-driven. This means having actionable information presented in context to surface insights, inform decisions, and elevate productivity, consistently and reliably. Our platform consists of packaged technology that allows this to happen quickly and without sacrificing context or quality as typically happens with “lossy” approaches involving data migration.

Let’s explore some of the best practices for becoming information-driven using intelligent search by leveraging the experience Sinequa has gained working with large customers within knowledge-intensive industries.

Pursue Ubiquitous Connectivity

An intelligent search solution should be able to find answers, information and insights wherever they might reside. In any significantly sized organization, this requires a broad portfolio of connectors and convertors to support ingesting and processing content and data from a diversity of repositories and business applications. With all of this content and data being ingested and updated on a regular basis, the resultant index can be optimized to connect information along topical lines.

Connecting information along topical lines across all repositories allows information-driven organizations to surface the collective expertise of the organization and make it transparent. This is especially valuable in large organizations that are geographically distributed. By connecting people with expertise, the overall responsiveness of the organization increases. This means everywhere, from the folks driving innovation in Research & Development, to the Service and Support folks helping customers, to the Marketing & Sales folks bringing in new business. The results can be spectacular. Time to proficiency decreases as new employees, and even existing employees learning new skills, have ready access to the expertise needed to take things to the next level.

Automate Interpretation of Meaning

A key to connecting information and surfacing meaning is linguistic processing, which performs a number of important functions, including:

♦ Automated language detection

♦ Lexical analysis (part of speech tagging, compound word detection) and syntactical analysis (disambiguation, lemmatization of nouns, verbs, adjectives)

♦ Automatic extraction of dozens of entity types, including Concepts and Named Entities like people, places, companies, etc.

♦ Text mining agents integrated into the indexing engine that detect regular expressions and/or complex “shapes” that describe the likely meaning of specific terms and phrases and then normalize them for use across the enterprise.