ML-based Telegram bot for real estate price prediction

Salem, Hamza; Mazzara, Manuel

doi:10.1088/1742-6596/1694/1/012010

Cited by 5 publications

(3 citation statements)

References 8 publications

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“…Here, we took advantage of the possibility of a simple interface through the use of a Telegram messenger bot. Recently, this type of application has become popular and is used for crowdsourcing problems in social research [ 84 ], for predicting real-estate prices [ 85 ], for determining the type of trees [ 86 ], etc. Its advantages are that there is no need to develop and maintain a smartphone graphical interface, and, at the same time, that it allows us to send an image as a request to a server for further processing and displaying the results.…”

Section: Discussionmentioning

confidence: 99%

Image-Based Wheat Fungi Diseases Identification by Deep Learning

Genaev

Сколотнева

Gultyaeva

et al. 2021

Plants

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Diseases of cereals caused by pathogenic fungi can significantly reduce crop yields. Many cultures are exposed to them. The disease is difficult to control on a large scale; thus, one of the relevant approaches is the crop field monitoring, which helps to identify the disease at an early stage and take measures to prevent its spread. One of the effective control methods is disease identification based on the analysis of digital images, with the possibility of obtaining them in field conditions, using mobile devices. In this work, we propose a method for the recognition of five fungal diseases of wheat shoots (leaf rust, stem rust, yellow rust, powdery mildew, and septoria), both separately and in case of multiple diseases, with the possibility of identifying the stage of plant development. A set of 2414 images of wheat fungi diseases (WFD2020) was generated, for which expert labeling was performed by the type of disease. More than 80% of the images in the dataset correspond to single disease labels (including seedlings), more than 12% are represented by healthy plants, and 6% of the images labeled are represented by multiple diseases. In the process of creating this set, a method was applied to reduce the degeneracy of the training data based on the image hashing algorithm. The disease-recognition algorithm is based on the convolutional neural network with the EfficientNet architecture. The best accuracy (0.942) was shown by a network with a training strategy based on augmentation and transfer of image styles. The recognition method was implemented as a bot on the Telegram platform, which allows users to assess plants by lesions in the field conditions.

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Section: Discussionmentioning

confidence: 99%

Image-Based Wheat Fungi Diseases Identification by Deep Learning

Genaev

Сколотнева

Gultyaeva

et al. 2021

Plants

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“…Bot is a program that can work automatically. In Telegram, bots mean special Telegram accounts in the form of channels designed to be able to handle and display messages automatically [18]. Users can interact with bot by sending messages or well known commands either through private messages or through groups.…”

Section: Literature Review Telegram Botmentioning

confidence: 99%

The Development of Telegram Bot Api to Maximize The Dissemination Process of Islamic Knowledge in 4.0 Era

et al. 2022

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Information technology is developing quickly in this era as if the world is in our hands. All forms of information can be accessed quickly, including Islamic information by utilizing internet technology. One of well-known medium to spread information is social media. Telegram, as one of the social media that has various beneficial features and widely used by people, has the potential to be a medium for disseminating Islamic knowledge. To improve the dissemination process of Islamic knowledge, we used one of the services found on Telegram namely chatbot. By utilizing Telegram Bot API, we make a bot that can automatically provide output according to the command given by the user in this case, giving various Islamic knowledges that users need such as Tafsir, hadith, daily prayer, and even Islamic history with a reliable source. Based on the testing result, the bot is showing a good result because it’s displaying the expected output and all features are working fine as they should be. We hoped that this bot can maximize the dissemination process of Islamic knowledge in Indonesia and reach wider audience coverage.

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“…Recently, machine learning and data mining algorithms such as decision tree regression, neural networks, support regression vector, fuzzy regression model, and multiple linear regression have been applied to predict real estate prices [5][6][7][8][9][10]. Proposed approaches have admirable techniques for prediction.…”

Section: Introductionmentioning

confidence: 99%

Data Analysis on the Influencing Factors of the Real Estate Price

He¹,

Chen²,

Xiao³

et al. 2021

Artificial Intelligence Evolution

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China has carried out a large number of real estate market reforms that change the real estate market demand considerably. At the same time, the real estate price has soared in some cities and has surpassed the spending power of many ordinary people. As the real estate price has received widespread attention from society, it is important to understand what factors affect the real estate price. Therefore, we propose a data analysis method for finding out the influencing factors of real estate prices. The method performs data cleaning and conversion on the used data first. To discretize the real estate price, we use the mean ± standard deviation (SD), mean ± 0.5 SD, and mean ± 2 SD of the price and divide it into three categories as the output variable. Then, we establish the decision tree and random forest model for six different situations for comparison. When the data set is divided into training data (70%) and testing data (30%), it has the highest testing accuracy. In addition, by observing the importance of each input variable, it is found that the main influencing factors of real estate price are cost, interior decoration, location, and status. The results suggest that both the real estate industry and buyers should pay attention to these factors to adjust or purchase real estate.

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ML-based Telegram bot for real estate price prediction

Cited by 5 publications

References 8 publications

Image-Based Wheat Fungi Diseases Identification by Deep Learning

Image-Based Wheat Fungi Diseases Identification by Deep Learning

The Development of Telegram Bot Api to Maximize The Dissemination Process of Islamic Knowledge in 4.0 Era

Data Analysis on the Influencing Factors of the Real Estate Price

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