{"id":2723422,"date":"2025-07-28T09:00:49","date_gmt":"2025-07-28T16:00:49","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2723422"},"modified":"2025-07-28T11:55:44","modified_gmt":"2025-07-28T18:55:44","slug":"from-keywords-to-context-enhancing-search-with-ai-in-business-analyst-pro","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/analytics\/from-keywords-to-context-enhancing-search-with-ai-in-business-analyst-pro","title":{"rendered":"From keywords to context: Enhancing search with AI in Business Analyst Pro"},"author":346602,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[23341,37171,430222],"tags":[],"industry":[],"product":[36711],"class_list":["post-2723422","blog","type-blog","status-publish","format-standard","hentry","category-analytics","category-business","category-retail","product-bus-analyst"],"acf":{"authors":[{"ID":346602,"user_firstname":"Crystal","user_lastname":"Harper","nickname":"Crystal Harper","user_nicename":"charper","display_name":"Crystal Harper","user_email":"charper@esri.com","user_url":"","user_registered":"2023-09-27 20:50:35","user_description":"Crystal is a Product Engineer with the Business Analyst Pro team. She leverages her skills in statistics and spatial data science to contribute to product development and deliver valuable solutions to customers.","user_avatar":""}],"short_description":"Discover how AI-driven semantic search in Business Analyst Pro enhances data exploration by providing context-driven results.","flexible_content":[{"acf_fc_layout":"content","content":"

AI, or artificial intelligence, is a hot topic right now. But what exactly is it, and why should you care? AI is a big field with several subsets including machine learning and natural language processing (NLP). Machine learning involves advanced math, statistics, data processing, model training, and model optimization. NLP utilizes machine learning algorithms to perform tasks that pertain to human language. One such task is semantic search (more on that later). AI is revolutionizing the way users interact with their data, allowing for more efficient exploration and deeper analysis.<\/p>\n

The ability to use AI-enhanced tools was added in ArcGIS Pro 3.3. This experience is entirely optional, and the user must opt-in during installation<\/a>. This article provides an overview of semantic search and illustrates its application within Business Analyst Pro.
\n <\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2777822,"id":2777822,"title":"semantic_search 1","filename":"semantic_search-1-1-scaled.jpg","filesize":141793,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/03\/semantic_search-1-1-scaled.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/analytics\/from-keywords-to-context-enhancing-search-with-ai-in-business-analyst-pro\/semantic_search-1-2","alt":"Semantic search visualization","author":"346602","description":"","caption":"Semantic search visualization","name":"semantic_search-1-2","status":"inherit","uploaded_to":2723422,"date":"2025-04-29 19:23:18","modified":"2025-04-29 19:24:52","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":2560,"height":1440,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/03\/semantic_search-1-1-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/03\/semantic_search-1-1-scaled.jpg","medium-width":464,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/03\/semantic_search-1-1-scaled.jpg","medium_large-width":768,"medium_large-height":432,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/03\/semantic_search-1-1-scaled.jpg","large-width":1920,"large-height":1080,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/03\/semantic_search-1-1-1536x864.jpg","1536x1536-width":1536,"1536x1536-height":864,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/03\/semantic_search-1-1-2048x1152.jpg","2048x2048-width":2048,"2048x2048-height":1152,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/03\/semantic_search-1-1-826x465.jpg","card_image-width":826,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/03\/semantic_search-1-1-1920x1080.jpg","wide_image-width":1920,"wide_image-height":1080}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

What is semantic search?<\/h3>\n

Traditionally, search engines utilize keyword search. A keyword search matches exact or partial words that the user queries. Semantic search uses natural language processing to return results based on context and meaning.<\/p>\n

Without diving too much into the technical aspects of semantic search and visiting the Ghost of Linear Algebra Class Past\u2122, the main idea with semantic search is that words and phrases are encoded as n<\/em>-dimensional vectors. Context and meaning can be derived based on where those vectors exist in n<\/em>-dimensional space. Using cosine similarity, we can see how closely related these vectors are, which helps us understand how similar, or dissimilar, the meanings of the words and phrases are. Mind-bending stuff\u2014if you like math. And if you don\u2019t, well, mind-numbing then?<\/p>\n

ANYWAY. The end result is cool and that\u2019s what matters! This fancy math allows us to generate meaningful and context-driven search results that are closer to human language. We’ve implemented this optional functionality in Business Analyst Pro so that searches for variables and points of interest aren’t limited to keywords. Semantic search provides a larger scope of results. With keyword search only, a variable query for climate change<\/code> yields only results that have the keyword climate change<\/code> in the variable name. Searching for climate changes<\/code> yields zero results. Adding an s<\/code> limited results drastically. With semantic search enabled, not only are the keyword search results returned, but so are variables that are related<\/em> to climate change. Now we see results that include psychographics pertaining to the environment. Searching for climate chang<\/code> or climate changes<\/code> also yields relevant results. This is where semantic search outshines keyword search.<\/p>\n

Using semantic search with Business Analyst Pro workflows and tools<\/h3>\n

With the introduction of AI-enhanced tools in ArcGIS Pro, semantic search functionality has been added to Business Analyst Pro. It enhances variable search in the data browser<\/a> and helps users find related points of interest in both the points of interest search workflow<\/a> and the Generate Points From Business Listings tool.<\/a><\/p>\n

 <\/p>\n

Getting started with semantic search in Business Analyst Pro<\/strong><\/p>\n

After installing ArcGIS Pro 3.3 or later with the optional semantic search feature<\/a>, the local datasets need to be configured with the resources necessary for semantic search functionality. Currently, this functionality works with the 2024 and 2025 U.S. datasets and the 2024 Canada dataset.<\/p>\n

Here\u2019s a quick rundown:<\/p>\n

    \n
  1. Install ArcGIS Pro 3.3 (or later) with the Semantic Search feature selected.<\/li>\n
  2. Download the dataset and the associated semantic search resources from My Esri.<\/li>\n
  3. Unzip the files.<\/li>\n<\/ol>\n

     
    \nThe less-quick rundown is in the setup instructions for the specific dataset:<\/p>\n