High-value-added travel content creation and distribution system based on customer sentiment analysis

Abstract

To provide an itinerary explanation support system that analyzes the semantic structure of an itinerary and automatically generates commercially available video content that appeals to customers' emotions and provides psychological healing. [Solution] The itinerary explanation support system applies natural language processing (NLP) to itinerary data and includes a semantic tag generation unit (30) that automatically generates scores for semantic tags using a sentiment dictionary. Based on these scores, a video generation unit (40) automatically controls the movements and facial expressions of the user-registered surrogate presence, generating high-value-added personalized video content. The control logic particularly links the "healing" tag with the sluggish movements of the surrogate presence, contributing to improved QOL.

Description

[Technical Field]

[0001] This invention relates to information processing technology that analyzes the semantic structure of travel itineraries and automatically generates commercially usable video content that appeals to customers' emotions and provides psychological healing, with the aim of applying it to sales promotion in travel-related businesses and the welfare and education fields. [Background technology]

[0002] Traditionally, information provided in travel-related businesses has been limited to conveying objective facts and functions, such as photos, videos, and route information of tourist spots. This has made it difficult to provide experiences that satisfy customers' inner feelings and latent travel needs (e.g., wanting to relieve daily fatigue, wanting to learn, etc.). As shown in Patent Document 1 (JP 2016-186986, etc.), there are systems that automatically generate video content based on itinerary data, but these technologies are limited to simply presenting information and have not made sufficient attempts to add emotional value to the content itself. Furthermore, as shown in Patent Document 2 (JP 2022-162890, etc.), although technology is known for analyzing a user's emotions and controlling the behavior of an avatar, this is primarily designed to respond to immediate emotions such as biological reactions, and was not intended to address the structure of "meaning" inherent in the entire journey or the long-term psychological needs (especially welfare-related healing) that derive from it. As a result, conventional technologies have not been able to effectively provide symbolic experiences that enable strong psychological healing and self-reflection for people who have difficulty traveling due to physical limitations or health reasons, and have not met social needs in this area. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Document number: JP 2016-186986 Technology for automatically generating video content of tourist spots based on travel itinerary information. Challenges (comparison points): Although the content is generated, it does not include avatar control that satisfies the viewer's emotional needs or creates psychological empathy. [Patent Document 2] Document number: JP 2022-162890 Technology that analyzes the user's biometric information and emotions to control the avatar's facial expressions and movements. Issues (points of comparison): It does not analyze the "meaning of the itinerary" of the user, and in particular does not take into account the welfare perspective of linking the "healing" tag with "slow movements," nor does it have any linkage with external itinerary information. [Non-patent literature]

[0004] [Non-Patent Document 1] Literature: Edited by the Japan Society for the Study of Emotional Sciences: "Emotional Sciences Vol. 25, No. 1, 2022" To show the current state of emotion analysis technology and the academic foundations regarding psychological effects. Summary of the Invention [Problem to be solved by the invention]

[0005] Extracting emotional needs from customer itinerary information and maximizing customer purchasing motivation and emotional satisfaction through video production using surrogate presence. At the same time, resolving welfare issues by providing symbolic experiences that enable strong psychological healing and self-reflection for people who cannot travel. [Means for solving the problem]

[0006] It is equipped with a semantic tag generation unit (30) that generates a score for a semantic tag (e.g., healing, learning) from the itinerary data, and an image generation unit (40) that automatically controls the movements and facial expressions of the user-registered surrogate based on the score to generate an image. In particular, it features a control logic for producing slow movements and gentle facial expressions that are linked to the "healing" score. [Effects of the Invention]

[0007] 1. Improved market competitiveness and profitability: Videos that are optimized to address customers' emotional needs will dramatically improve product booking rates, customer engagement, and profitability across the travel business. 2. Contribution to the welfare and medical fields and development of new markets (public benefit): For people who have difficulty traveling due to physical limitations or health reasons, the surrogate presence's emotional linkage control provides a powerful psychological healing and self-projection effect, contributing to improving their quality of life (QOL). This effect will establish a new market for licensing sales to medical and nursing care facilities and the rehabilitation field. 3. Applications in the fields of education and public relations: By using educational tags and surrogate presence induction, immersive and effective learning content can be automatically generated, opening up new commercial markets for educational institutions and local governments. [Brief explanation of the drawings]

[0008] [Figure 1] This shows the overall configuration of the itinerary explanation support system according to the present invention. In addition to a series of processing flows from itinerary data acquisition and analysis, semantic tag generation, video generation, and output, it also includes a linkage structure with a proxy presence registration UI and an education mode presentation unit. [Figure 2] This diagram shows in flowchart form the specific processing steps from itinerary data acquisition to final video output. The function and processing order of each step are clarified, and the characteristic processing of the invention, such as semantic tag generation and surrogate presence control, is particularly emphasized. [Figure 3] This figure shows an example of the internal structure of itinerary data to be analyzed in this invention. In particular, it clarifies how information such as "basic tags," "semantic tag scores," and "education tags" is stored for each destination. [Figure 4] This is a conceptual diagram showing how the semantic structure of an itinerary is spatially presented from the perspective of a user wearing an AR / VR headset. [Figure 5]This diagram shows an example of the configuration of the "education mode," which presents educational information overlaid on video content. This configuration presents educational elements such as geography, culture, language, and emotion as UI overlays on a video in which a surrogate experiences a journey. [Figure 6] This diagram shows the configuration in which the actions, expressions, and visual effects of the surrogate presence are automatically linked based on the semantic tag score. [Figure 7] This figure shows an example of the internal structure of itinerary data to be analyzed in this invention. In particular, it clarifies how information such as "basic tags," "semantic tag scores," and "education tags" is stored for each destination. DETAILED DESCRIPTION OF THE INVENTION

[0009] As shown in Figure 1, this system is composed of an itinerary data acquisition unit (10), an analysis unit (20), a semantic tag generation unit (30), a video generation unit (40), a video output unit (50), a proxy presence registration UI (60), and an educational mode presentation unit (70). 1. Details of the Semantic Tag Generation Algorithm (30) The semantic tag generation unit (30) applies natural language processing (NLP) to the text information and calculates semantic tag scores such as "healing," "learning," and "moving" using a sentiment dictionary and topic model. It also weights the user's stay time and user attribute information to determine the main semantic tag. 2. Details of the Surrogate Presence Control Algorithm (40) The image generation unit (40) automatically controls the actions, facial expressions, and movement paths of the surrogate being based on the main semantic tags. - Implementation of "healing" control: If the main semantic tag is "healing," the surrogate entity's movement speed will be slowed down to 50% of the normal speed, and an animation with a calm expression and narrowed eyes will be selected. This will give a sense of peace and security to people who cannot travel. - Concrete control of "emotion": When the main semantic tag is "emotion," the surrogate being is given the action of stopping and looking up at the scenery, promoting empathy in the viewer. 3. Specific actions for the collaboration between education and public relations (70) When an education tag is assigned, the education mode presentation unit (70) is activated and presents information on geography, history, culture, etc. The image generation unit (40) guides the gaze and gestures of the surrogate being toward the information, increasing the attention of learning and public relations information. [Example]

[0010] This invention not only contributes to increasing the profits of travel-related businesses in general, but can also be licensed to medical, nursing care, and rehabilitation facilities as healing content aimed at improving quality of life. It also contributes to effective public relations activities by educational institutions and local governments. [Industrial Applicability]

[0011] 1. Applications in the travel industry By adding a new dimension of emotion analysis to customer itinerary information, this invention makes it possible to provide high-value-added services not available in conventional travel content. Enhanced sales promotion: By linking the actions and facial expressions of a surrogate (pet, character, etc.) based on the travel itinerary intention and the customer's latent emotional needs (healing, learning, inspiration), psychological empathy with the customer and their willingness to purchase are dramatically improved. Use by OTAs (Online Travel Agencies): By incorporating it into promotional videos and AR / VR content for existing travel products, you can differentiate your products from competitors and directly increase booking rates and customer engagement. Providing personalized travel experiences: By providing optimal video presentations tailored to each customer's emotional score when preparing for or reviewing a trip, or when reflecting on a trip afterward, we can encourage repeat use and become a source of ongoing revenue. 2. Expansion into the fields of welfare, medicine, and education The core technology of this invention, "automatic control of surrogate presence based on emotion tags," has great potential to contribute to solving social issues beyond the travel industry. Welfare and medical support: For people who have difficulty traveling or going out due to physical or mental limitations, a surrogate being can act as a proxy and empathize with their emotions, providing a symbolic outing experience and strong psychological healing. This can improve quality of life (QOL) and can be applied as a non-pharmacological therapy in psychiatric and nursing care facilities. Application to education and public relations: By using the educational mode (70), which presents information corresponding to educational tags (history, geography, etc.) derived from semantic tags in the video in conjunction with the gaze and gestures of a surrogate being, it can be used as an effective teaching material to increase motivation to learn and solidify the information in memory. [Explanation of symbols]

[0012] 10: Itinerary data acquisition unit, 20: Itinerary data analysis unit, 30: Semantic tag generation unit, 40: Video generation unit, 50: Video output unit, 60: Proxy presence registration UI, 70: Education mode presentation unit

Claims

1. A high-value-added travel content generation and distribution system based on customer sentiment analysis, comprising: an itinerary data acquisition unit (10) that receives itinerary data including itinerary information; a semantic tag generation unit (30) that generates scores of multiple semantic tags that indicate the purpose and emotion of the itinerary based on the itinerary data; a proxy presence data acceptance unit (60) that receives proxy presence data registered in advance by a user; and a video generation unit (40) that automatically controls at least one of the actions, facial expressions, and route of the proxy presence in conjunction with the semantic tag scores and outputs a video.

2. 2. The system according to claim 1, wherein the semantic tag generation unit (30) applies natural language processing (NLP) to text information included in the itinerary data and analyzes it using a sentiment polarity dictionary to generate scores for at least three semantic tags, namely, “healing,” “learning,” and “moving,” and the image generation unit (40) performs control based on the main semantic tag with the highest score among the semantic tags.

3. The system according to claim 2, wherein the image generation unit (40) controls the surrogate being to have a slow walking animation with a reduced speed of movement of 20% to 50% of its normal speed and a calm facial expression when the main meaning tag is "healing."

4. The system described in claim 2 or 3, characterized in that it further comprises an **educational mode presentation unit (70)** that outputs related information (at least one of geography, history, and culture) within the video based on educational tags that indicate educational information derived from the semantic tags.

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