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Authors
Amaresh V,Balaji,Channakeshava L,Manoj,Mrs. Gajulapalli latheswari
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Keywords
Adaptive Dream Journey Analyzer, Artificial Intelligence (AI), Natural Language Processing (NLP), Dream Analysis, Conversational Agents, Adaptive Systems, Machine Learning (ML), Deep Learning, Intent Recognition, Named Entity Recognition (NER), Sentiment Analysis, Emotion Detection, Personalization, Contextual Understanding, Natural Language Understanding (NLU), Natural Language Generation (NLG), Human-Computer Interaction (HCI), Automated Interpretation, Dialogue Management, Psychological Asses
Abstract
This paper presents the Adaptive Dream Journey Analyzer (ADJA). This advanced AI platform
leverages Natural Language Processing (NLP) and adaptive algorithms to interpret and analyze user-described dream experiences with remarkable contextual accuracy. In the modern era, where understanding
The subconscious mind is growing in both clinical and personal significance. ADJA distinguishes itself by
enabling dynamic, human-like interpretation of highly subjective dream narratives. [1] The system is
engineered to comprehend, process, and generate insightful feedback on dream content, facilitating
automated analysis for psychological insight, creativity enhancement, or digital self-reflection. ADJA
employs sophisticated NLP techniques, including intent recognition (to understand the user's reflection
aims), named entity recognition (extracting dates, characters, and settings from dreams), sentiment analysis
(capturing the emotional undertone), and advanced contextual modeling, which preserves narrative
coherence throughout a session.
[2] personalized recommendations, and automating routine tasks.
Blending state-of-the-art machine learning with rule-based interpretation patterns, ADJA adapts to
unique user profiles and personal symbolism, delivering an evolving and personalized interpretation
experience over time. Its applicability spans clinical psychology (assisting therapists with dream content
exploration), creative industries (stimulating story generation and art), wellness technology (aiding with
self-awareness and nightly mood tracking), and consumer-facing dream journaling tools. [3] (keeping the
conversation coherent). The system combines machine learning models and rule-based logic, creating a
hybrid approach that improves its adaptability and performance over time
This work demonstrates how combining adaptive AI and modern NLP expands our potential to decode
dream experiences, making subconscious analysis more accessible, engaging, and actionable than ever
before. This project shows how using modern AI and NLP can improve user interaction and engagement
through advanced automated dialogue systems.
IJCRT's Publication Details
Unique Identification Number - IJCRT2509100
Paper ID - 293488
Author type - Indian Author
Page Number(s) - a818-a831
Pubished in - Volume 13 | Issue 9 | September 2025
DOI (Digital Object Identifier) -
No Of Downloads - 32
Author Country - India, 560035, Bangalore, Bangalore, 560035, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
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Amaresh V,Balaji,Channakeshava L,Manoj,Mrs. Gajulapalli latheswari, "Adaptive Dream Journey Analyzer", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 9, pp.a818-a831, September 2025, Available at :http://www.ijcrt.org/papers/IJCRT2509100.pdf
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