ProCogia used NLP and machine learning to optimize image search accuracy
Company Information
A premier global visual media company faced challenges with its image search functionality, where users often encountered difficulties finding relevant results due to ambiguous search intents, incorrect query parsing, and inaccurate or missing metadata. ProCogia was tasked with optimizing the search experience by employing advanced NLP and ML technologies to understand and improve the accuracy and relevance of search results, thereby enhancing user satisfaction and driving key business metrics.
The Challenge
The primary challenge was to accurately interpret user search queries, which often suffered from ambiguity, misinterpretation, and a lack of relevant metadata linking them to the correct images. These issues led to suboptimal search experiences, affecting customer engagement and asset purchase rates. The solution required a deep understanding of linguistics, user intent, and the systematic refinement of search algorithms to deliver significantly improved outcomes.
Procogia’s Approach
ProCogia analyzed user queries to identify the main categories of failed searches, which were: Ambiguous search intent, Incorrect parsing of search queries, Inaccurate or missing metadata.
We designed and implemented the search parsing algorithm – matching search queries to concepts in the search ontology – that eliminated or mitigated several major causes of suboptimal results.
We created and analyzed a representative dataset of suboptimal searches and used this to identify and address systematic sources of search failure in image metadata, such as incorrect lemmatization.
ProCogia’s engagement continues with the client to improve searching by deploying foundational models and multimodal embeddings to capture highly relevant contextual information between the query and the returned images. This ensures irrelevant images are not presented to the user.
The Results
Through rigorous hypothesis testing we have helped our client identify the underlying causes of the search challenges.
We developed and deployed a range of linguistics and AI solutions to improve query understanding, and improve the searching and browsing experience for users, while driving key conversion metrics (customer engagement and asset purchase).
Our NLP machine learning model uses cosine similarity to identify best matches between search queries and images in the database, greatly improving the accuracy of ambiguous queries.
ProCogia’s solution allows our client’s customers to see a higher number of relevant search results (improved recall) and reduces incorrect results (greater precision).
Services Used
Data Science
Services Used Data Science We use open source technology to leverage the full potential of your data. Predictive and prescriptive results are actioned using AI and Machine Learning (ML).
Data Consultancy
We provide data consultancy to organizations to optimize your investment in people, processes, and technology. This is typically through data strategy engagements, roadmaps, transformations, and independent technology advice.
Data Engineering
We partner with all major cloud providers, allowing us to adopt a data-agnostic approach focused on delivering tailored game-changing solutions.
Conclusion
ProCogia’s application of NLP and ML technologies to optimize image search accuracy for a global visual media company represents a significant advancement in search technology, directly impacting user satisfaction and business performance. By addressing the root causes of search challenges and continuously refining the search experience, ProCogia has demonstrated its expertise in transforming complex data problems into actionable solutions, underscoring the vital role of data science in enhancing digital platforms and driving business success.
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