Evolving search behaviors on the web
As people search online, the way they search is changing, and search engines are adjusting to keep up. The following are some key ways people search for information in recent times:
- Intent-Driven: Instead of typing exact keywords, users now express their needs with phrases like I want to or I need to. Modern search engines understand the purpose behind these phrases and give more relevant results.
- Ranked Results: Search results are organized based on what other users found helpful. This means the most useful content appears at the top, making it easier to find quality information.
- Multiple Sources: The more sources a search engine covers, the better the results. By pulling information from a variety of trusted sources, search engines provide more complete and accurate answers.
- Personalized: Search engines adjust results based on factors like time, location, and user preferences. This makes it easier for users to find information that fits their specific needs at the moment.
Why Adobe Learning Manager’s search is better
Adobe Learning Manager offers a smarter, more advanced search experience. It not only matches keywords but also contextually understands the meaning of user queries to find the most relevant results.
- AI-Powered: Adobe Learning Manager uses advanced AI techniques to understand the meaning behind search intent and not just the words. This helps show results that really match what the user wants, making searches more accurate.
- Peer-Driven: Adobe Learning Manager uses a range of course quality parameters to rank the most useful results. This ranking algorithm is trained on 50 million data points that periodically scores every content in the repository
- Comprehensive: Adobe Learning Manager searches the entire library, including own content, third-party course titles, descriptions, tags, personalized notes and other metadata. For content like Video and PDF, it automatically transcribes and searches within their transcript.
Adobe Learning Manager’s AI-powered search
Adobe Learning Manager uses advanced AI technology to enhance the search experience and make it easier to find relevant learning content. The major components of advanced search are described below.
Recognizing key terms
Adobe Learning Manager uses Natural Language Processing (NLP) to identify the important keywords from course titles and descriptions. It then focuses on those keywords to provide better search results, helping boost the results with those keywords over other results. For example, if a learner searches for PhotoShop Basics, Adobe Learning Manager will prioritize the word PhotoShop to show the most relevant courses.
Prioritize the keyword
In the screenshot above, a learner searches for courses using the term PhotoShop getting started. The search prioritizes the word PhotoShop to find the most relevant courses around PhotoShop. For the keyword getting started, it understands the intent and looks for similar words to show the best matches. This way, the learner sees courses that focus on PhotoShop and are suitable for beginners.
Expanding the query
Adobe Learning Manager expands the user query to more contextual meaning to help find better results. This way the search algorithm gets more context along with the user query. Even if learners use general terms, they can still find useful results. For example, if a learner is searching for Customer service foundations, it tries to find the keyword from the query and expand the rest of the query to similar phrases.
Expanding the query
Course metadata search
Adobe Learning Manager’s metadata search covers metadata from both native and imported courses (e.g. from LinkedIn Learning or Go1). This capability searches through your course titles, descriptions, tags, personalized notes, and other metadata. This helps make the results better and more accurate by using a lot of different metadata to find results.
Note: Customer data, including content and transcripts, is not shared with any external service for AI-powered search. All content is stored within the current storage system.
In-Content search
Adobe Learning Manager features enhanced search capabilities that allow users to search within the actual content of various file types, including videos, audio files, PDFs, documents, presentations, and spreadsheets. The system automatically transcribes this content to provide more comprehensive and accurate search results. Additionally, recordings from Adobe Connect meetings are incorporated into the search, ensuring that valuable information is not missed. If a match is found within the content, the search model boosts the ranking of that content in final results. The final ranking is determined by multiple factors, as outlined in the AI-Powered search and re-ranking section.
Semantic search
Adobe Learning Manager now incorporates semantic search alongside traditional lexical search, enhancing the accuracy of search results. By generating vector embeddings from course titles and descriptions, it creates a comprehensive vector database. When a learner submits a query, the system vectorizes the query and performs similarity matching to identify the most relevant results. For example, if a learner searches for beginner PhotoShop tutorial, the system understands the request and finds courses that are especially helpful for PhotoShop beginners .
Semantic search