It's a powerful version of linebot

Overview

CTPS-FINAL

Linbot-sever.py

主程式

Algorithm.py

推薦演算法,媒合餐廳端資料與顧客端資料

config.ini

儲存 channel-access-token、channel-secret 資料

Preface

生活在成大將近4年,我們每天的午餐時間看著形形色色的店家,看似玲瑯滿目卻都吃膩了,中午覓食已經從期待變成壓力,每天問著「待會吃什麼?」,然後花費大量時間和心力,還是不知道要午餐吃什麼。因此我們希望運用Computational Thinking and Problem Solving 的思維,幫助大家解決這個困擾已久的問題。

Problem Definition

My target problem - 解決成大師生不知道午餐吃什麼的困擾?

Problem Decomposition

  • :成大師生
  • :午餐煩惱
  • :週一到週五 11點 ~ 14點
  • :成大周遭 1.5km 以內距離
  • constrain : 交通限制(交通工具)、店家營業時間限制、用戶人數(餐廳是否能容納)、預計等待及用餐時間

Pattern Recognition

  1. 大家通常到正餐時間才會想要吃甚麼
  2. 大家移動的距離有限,如果下午1點還有課,就會在學校附近用餐
  3. 同類型食物太頻繁吃會吃膩
  4. 學生會考慮cp值(有價格區間考量)
  5. 如果店家以人潮眾多就傾向換一間店家
  6. 會因為天氣而影響選擇(例如很熱,就會找有冷氣的餐廳)
  7. 朋友或認識的同學會一起用餐

Abstraction

(把Problem Decomposition的細項問題化)

  • 店家資料
      1. 如何取得店家資料?
      1. 如何確保店家資料即時性?
  • 用戶資料
      1. 如何取得用戶資料?
      1. 如何做到使用者優化?
  • 演算法
      1. 如何根據實際狀況設計演算法
      1. 怎麼測試演算法結果是否符合用戶需求
  • 訊息回推
      1. 用什麼管道回送推薦清單
      1. 介面如何優化
      1. 怎麼得知用戶實際使用情況

Algorithm

  • 店家資料
    • 如何取得店家資料?
      • 利用 google maps 爬蟲
      • 實地探索(地點限制在成大周圍,所以有一定可行性)
    • 如何確保店家資料即時性?
      • 設計用戶回報機制
      • 定期網路爬蟲
  • 用戶資料
    • 如何取得用戶資料?
      • 利用 linbot 與使用者溝通,取得使用者需求
    • 如何做到使用者優化?
      • 利用 richmenus 串接 linbot,藉由圖文選單輸入
  • 演算法
    • 如何根據實際狀況設計演算法
      • 找外在生活條件(例如 : 天氣很熱,那冷氣的需求權重就提高一點)
    • 怎麼測試演算法結果是否符合用戶需求
      • 請朋友實際使用,並根據意見做出修改
  • 訊息回推
    • 用什麼管道回送推薦清單
      • Linebot
    • 介面如何優化
      • 建置模板按鈕,讓畫面看起來乾淨一點
    • 怎麼得知用戶實際使用情況
      • 設計用戶評分機制
      • 根據用戶評分或意見,進行修正

Solution Proposal

final report ppt & demo

References

Official repository for the paper F, B, Alpha Matting

FBA Matting Official repository for the paper F, B, Alpha Matting. This paper and project is under heavy revision for peer reviewed publication, and s

Marco Forte 404 Jan 05, 2023
Lingvo is a framework for building neural networks in Tensorflow, particularly sequence models.

Lingvo is a framework for building neural networks in Tensorflow, particularly sequence models.

2.7k Jan 05, 2023
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)

S2-BNN (Self-supervised Binary Neural Networks Using Distillation Loss) This is the official pytorch implementation of our paper: "S2-BNN: Bridging th

Zhiqiang Shen 52 Dec 24, 2022
TensorFlow (Python) implementation of DeepTCN model for multivariate time series forecasting.

DeepTCN TensorFlow TensorFlow (Python) implementation of multivariate time series forecasting model introduced in Chen, Y., Kang, Y., Chen, Y., & Wang

Flavia Giammarino 21 Dec 19, 2022
Multi-View Radar Semantic Segmentation

Multi-View Radar Semantic Segmentation Paper Multi-View Radar Semantic Segmentation, ICCV 2021. Arthur Ouaknine, Alasdair Newson, Patrick Pérez, Flore

valeo.ai 37 Oct 25, 2022
This is the official implement of paper "ActionCLIP: A New Paradigm for Action Recognition"

This is an official pytorch implementation of ActionCLIP: A New Paradigm for Video Action Recognition [arXiv] Overview Content Prerequisites Data Prep

268 Jan 09, 2023
Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model

Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model About This repository contains the code to replicate the syn

Haruka Kiyohara 12 Dec 07, 2022
FeTaQA: Free-form Table Question Answering

FeTaQA: Free-form Table Question Answering FeTaQA is a Free-form Table Question Answering dataset with 10K Wikipedia-based {table, question, free-form

Language, Information, and Learning at Yale 40 Dec 13, 2022
Code to reproduce the results for Statistically Robust Neural Network Classification, published in UAI 2021

Code to reproduce the results for Statistically Robust Neural Network Classification, published in UAI 2021

1 Jun 02, 2022
Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GanFormer and TransGan paper

TransGanFormer (wip) Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GansFormer and TransGan paper. I

Phil Wang 146 Dec 06, 2022
The implementation of PEMP in paper "Prior-Enhanced Few-Shot Segmentation with Meta-Prototypes"

Prior-Enhanced network with Meta-Prototypes (PEMP) This is the PyTorch implementation of PEMP. Overview of PEMP Meta-Prototypes & Adaptive Prototypes

Jianwei ZHANG 8 Oct 14, 2021
Next-gen Rowhammer fuzzer that uses non-uniform, frequency-based patterns.

Blacksmith Rowhammer Fuzzer This repository provides the code accompanying the paper Blacksmith: Scalable Rowhammering in the Frequency Domain that is

Computer Security Group @ ETH Zurich 173 Nov 16, 2022
Neural Tangent Generalization Attacks (NTGA)

Neural Tangent Generalization Attacks (NTGA) ICML 2021 Video | Paper | Quickstart | Results | Unlearnable Datasets | Competitions | Citation Overview

Chia-Hung Yuan 34 Nov 25, 2022
This repo is to be freely used by ML devs to check the GAN performances without coding from scratch.

GANs for Fun Created because I can! GOAL The goal of this repo is to be freely used by ML devs to check the GAN performances without coding from scrat

Sagnik Roy 13 Jan 26, 2022
TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision

TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision @misc{you2019torchcv, author = {Ansheng You and Xiangtai Li and Zhen Zhu a

Donny You 2.2k Jan 06, 2023
This is a work in progress reimplementation of Instant Neural Graphics Primitives

Neural Hash Encoding This is a work in progress reimplementation of Instant Neural Graphics Primitives Currently this can train an implicit representa

Penn 79 Sep 01, 2022
The implementation of CVPR2021 paper Temporal Query Networks for Fine-grained Video Understanding, by Chuhan Zhang, Ankush Gupta and Andrew Zisserman.

Temporal Query Networks for Fine-grained Video Understanding 📋 This repository contains the implementation of CVPR2021 paper Temporal_Query_Networks

55 Dec 21, 2022
Learning-Augmented Dynamic Power Management

Learning-Augmented Dynamic Power Management This repository contains source code accompanying paper Learning-Augmented Dynamic Power Management with M

Adam 0 Feb 22, 2022
天勤量化开发包, 期货量化, 实时行情/历史数据/实盘交易

TqSdk 天勤量化交易策略程序开发包 TqSdk 是一个由信易科技发起并贡献主要代码的开源 python 库. 依托快期多年积累成熟的交易及行情服务器体系, TqSdk 支持用户使用极少的代码量构建各种类型的量化交易策略程序, 并提供包含期货、期权、股票的 历史数据-实时数据-开发调试-策略回测-

信易科技 2.8k Dec 30, 2022
Clustering with variational Bayes and population Monte Carlo

pypmc pypmc is a python package focusing on adaptive importance sampling. It can be used for integration and sampling from a user-defined target densi

45 Feb 06, 2022