Group-Buying Recommendation for Social E-Commerce

Related tags

Recommender Systemsrecommender-systemrecommendationgraph-neural-networksgroup-buying
Overview

Group-Buying Recommendation for Social E-Commerce

This is the official implementation of the paper Group-Buying Recommendation for Social E-Commerce (PDF) accepted by ICDE'2021.

Group-Buying Dataset

Group buying, as an emerging form of purchase in social e-commerce websites, such as Pinduoduo.com , has recently achieved great success. In this new business model, users, initiator, can launch a group and share products to their social networks, and when there are enough friends, participants, join it, the deal is clinched. Group-buying recommendation for social ecommerce, which recommends an item list when users want to launch a group, plays an important role in the group success ratio and sales.

The information about the dataset can be found in BeiBei/readme.txt.

Code

We separate model definition from the framework librecframework for easily understanding.

You can find the framework librecframework in https://github.com/Sweetnow/librecframework.

Both modules mentioned in requirements.txt and librecframework should be installed before running the code.

More details about our codes will be added soon.

Usage

  1. Download both librecframework and this repo
git clone [email protected]:Sweetnow/librecframework.git
git clone [email protected]:Sweetnow/group-buying-recommendation.git
  1. Install librecframework (Python >= 3.8)
cd librecframework/
bash install.sh

  1. Install dgl

  2. Download negative.zip from Release, unzip it and copy *.negative.txt to datasets/BeiBei/

wget https://github.com/Sweetnow/group-buying-recommendation/releases/download/v1.0/negative.zip
unzip negative.zip
cp negative/* ${PATH-TO-GROUP-BUYING-RECOMMENDATION}/datasets/BeiBei

PS: negative sampling file is used for testing. More details can be found in Datasets README

  1. Set config/config.json and config/pretrain.json following Docs.

  2. Run the following command to know the CLI and check python environment:

python3 GBGCN train -h
# or
# python3 GBGCN test -h

PS: If you set hyperparameters that support multi input to multi values, the framework will automatically do grid-search accroding to your input. That is, use the Cartesian product of the hyperparameters for training and testing. For example, set --lr 0.1 0.01 -L 1 2, the codes will train and test model with hyperparameters [(0.1, 1), (0.1, 2), (0.01, 1), (0.01, 2)].

Citation

If you want to use our codes or dataset in your research, please cite:

@inproceedings{zhang2021group,
  title={Group-Buying Recommendation for Social E-Commerce},
  author={Zhang, Jun and Gao, Chen and Jin, Depeng and Li, Yong},
  booktitle={2021 IEEE 37th International Conference on Data Engineering (ICDE)},
  year={2021},
  organization={IEEE}
}

Acknowledgement

Comments
  • About Testing

    About Testing

    Hi,

    Since I always fail to run the testing mode (for both GBMF and GBGCN) due to lack of "model.json", I'm wondering how to save a pretrained (GBMF) model as a json file and how to run the testing mode. Thanks.

    opened by vincenttsai2015 16
  • About negative samples for testing

    About negative samples for testing

    Hi,

    After resolving the issues of testing execution, I'm wondering if the following error is due to the lack of test.negative.txt.

    image

    If so, how can I generate negative samples? Thanks.

    opened by vincenttsai2015 14
  • It was killed before the training process started when the code was reproduced

    It was killed before the training process started when the code was reproduced

    hello，I want to know what the computer configuration should be to successfully reproduce these jobs. I can't reproduce it on 2080ti with 11gb of memory, and it's useless when I try to make the batchsize small enough. Or can you specify the hyperparameter setting?

    opened by ZQSong1997 6
  • Implementing the GBGCN in google colab

    Implementing the GBGCN in google colab

    Hi, After installing setup.py file from the mentioned frame work in the GitHub, I tried to run the GBGCN.py file by this command in Google Colab, "! python GBGCN.py train --tag 'true' --SL2 0.001 --L2 0.001 --lr 1e-2 --layer 2 --alpha 0.6 --beta 0.01 ". The below Errors showed: ( Any help to solve these errors and run the file properly would be appreciated! Just to mentioned that when I tried to run the whole data on GBGCN.py, it was not successful. I think the not enough RAM on colab was the problem( my colab RAM is around 12 GB) so I tried to reduce the size of BeiBei data set( 0.01 of the data set) to tackle this issue. Then these errors showed)

    INFO:root:Environment Arguments(OrderedDict([('dataset', 'BeiBei'), ('device', [0]), ('sample_epoch', 500), ('sample_worker', 16), ('epoch', 500), ('tag', 'true')])) INFO:root:Dataloader Arguments(OrderedDict([('batch_size', 4096), ('batch_worker', 2), ('test_batch_size', 128), ('test_batch_worker', 2)])) INFO:root:Hyperparameter Arguments(OrderedDict([('embedding_size', 32), ('act', 'sigmoid'), ('pretrain', True), ('SL2', [0.001]), ('L2', [0.001]), ('lr', [0.01]), ('layer', [2]), ('alpha', [0.6]), ('beta', [0.01])])) INFO:root:{'comment': '固定参数', 'user': 'user', 'visdom': {'server': '127.0.0.1', 'port': {'BeiBei_itemrec': 16670, 'BeiBei_grouprec': 16670, 'BeiBei_SIGR': 16670, 'BeiBei': 16670, 'comment': '16671 is temporary'}}, 'training': {'test_interval': 5, 'early_stop': 50, 'overfit': {'protected_epoch': 10, 'threshold': 1}}, 'dataset': {'path': './BeiBei', 'seed': 123, 'use_backup': True}, 'logger': {'path': './log', 'policy': 'best'}, 'metric': {'target': {'type': 'NDCG', 'topk': 10}, 'metrics': [{'type': 'Recall', 'topk': 3}, {'type': 'Recall', 'topk': 5}, {'type': 'Recall', 'topk': 10}, {'type': 'Recall', 'topk': 20}, {'type': 'NDCG', 'topk': 3}, {'type': 'NDCG', 'topk': 5}, {'type': 'NDCG', 'topk': 10}, {'type': 'NDCG', 'topk': 20}]}} INFO:root:{'BeiBei': {'GBMF': ''}} DEBUG:root:Load BeiBei/BeiBei/BeiBei-neg-500-123-default.pkl DEBUG:root:finish loading neg sample INFO:root:GPU search space: [0] INFO:root:Auto select GPU 0 WARNING:visdom:Setting up a new session... Exception in user code:

    Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/urllib3/connection.py", line 159, in _new_conn (self._dns_host, self.port), self.timeout, **extra_kw) File "/usr/local/lib/python3.7/dist-packages/urllib3/util/connection.py", line 80, in create_connection raise err File "/usr/local/lib/python3.7/dist-packages/urllib3/util/connection.py", line 70, in create_connection sock.connect(sa) ConnectionRefusedError: [Errno 111] Connection refused

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/urllib3/connectionpool.py", line 600, in urlopen chunked=chunked) File "/usr/local/lib/python3.7/dist-packages/urllib3/connectionpool.py", line 354, in _make_request conn.request(method, url, **httplib_request_kw) File "/usr/lib/python3.7/http/client.py", line 1277, in request self._send_request(method, url, body, headers, encode_chunked) File "/usr/lib/python3.7/http/client.py", line 1323, in _send_request self.endheaders(body, encode_chunked=encode_chunked) File "/usr/lib/python3.7/http/client.py", line 1272, in endheaders self._send_output(message_body, encode_chunked=encode_chunked) File "/usr/lib/python3.7/http/client.py", line 1032, in _send_output self.send(msg) File "/usr/lib/python3.7/http/client.py", line 972, in send self.connect() File "/usr/local/lib/python3.7/dist-packages/urllib3/connection.py", line 181, in connect conn = self._new_conn() File "/usr/local/lib/python3.7/dist-packages/urllib3/connection.py", line 168, in _new_conn self, "Failed to establish a new connection: %s" % e) urllib3.exceptions.NewConnectionError: <urllib3.connection.HTTPConnection object at 0x7fd8435d5c50>: Failed to establish a new connection: [Errno 111] Connection refused

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/requests/adapters.py", line 449, in send timeout=timeout File "/usr/local/lib/python3.7/dist-packages/urllib3/connectionpool.py", line 638, in urlopen _stacktrace=sys.exc_info()[2]) File "/usr/local/lib/python3.7/dist-packages/urllib3/util/retry.py", line 399, in increment raise MaxRetryError(_pool, url, error or ResponseError(cause)) urllib3.exceptions.MaxRetryError: HTTPConnectionPool(host='127.0.0.1', port=16670): Max retries exceeded with url: /env/GBGCN_true-32-0.01-0.001-0.001-2-0.6-0.01-sigmoid-True-True (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7fd8435d5c50>: Failed to establish a new connection: [Errno 111] Connection refused'))

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/visdom/init.py", line 711, in _send data=json.dumps(msg), File "/usr/local/lib/python3.7/dist-packages/visdom/init.py", line 677, in _handle_post r = self.session.post(url, data=data) File "/usr/local/lib/python3.7/dist-packages/requests/sessions.py", line 578, in post return self.request('POST', url, data=data, json=json, **kwargs) File "/usr/local/lib/python3.7/dist-packages/requests/sessions.py", line 530, in request resp = self.send(prep, **send_kwargs) File "/usr/local/lib/python3.7/dist-packages/requests/sessions.py", line 643, in send r = adapter.send(request, **kwargs) File "/usr/local/lib/python3.7/dist-packages/requests/adapters.py", line 516, in send raise ConnectionError(e, request=request) requests.exceptions.ConnectionError: HTTPConnectionPool(host='127.0.0.1', port=16670): Max retries exceeded with url: /env/GBGCN_true-32-0.01-0.001-0.001-2-0.6-0.01-sigmoid-True-True (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7fd8435d5c50>: Failed to establish a new connection: [Errno 111] Connection refused')) INFO:visdom:Socket refused connection, running socketless ERROR:visdom:[Errno 111] Connection refused ERROR:websocket:error from callback <function Visdom.setup_socket..on_close at 0x7fd84346ec20>: on_close() takes 1 positional argument but 3 were given File "/usr/local/lib/python3.7/dist-packages/websocket/_app.py", line 407, in _callback callback(self, *args) Traceback (most recent call last): File "GBGCN.py", line 556, in torch.optim.SGD) File "/usr/local/lib/python3.7/dist-packages/librecframework-1.3.0-py3.7.egg/librecframework/pipeline.py", line 633, in during_running model_class, other_args, trainhooks, optim_type) File "/usr/local/lib/python3.7/dist-packages/librecframework-1.3.0-py3.7.egg/librecframework/pipeline.py", line 239, in during_running model.load_pretrain(self._pretrain[self._eam['dataset']]) File "GBGCN.py", line 102, in load_pretrain pretrain = torch.load(path, map_location='cpu') File "/usr/local/lib/python3.7/dist-packages/torch/serialization.py", line 381, in load f = open(f, 'rb') FileNotFoundError: [Errno 2] No such file or directory: ''

    opened by Ali-khn 5
  • About ranking metric evaluation

    About ranking metric evaluation

    Hi,

    I'm wondering if it is possible to evaluate the ranking metrics of MAP(mean average precision) @ K and HR(hit ratio) @ K of GBMF/GBGCN under librecframework. If yes, how can I modify the code? Thanks.

    opened by vincenttsai2015 2
  • 您好，我在复现您的代码时遇到以下问题，想请教一下。

    您好，我在复现您的代码时遇到以下问题，想请教一下。

    命令： python GBGCN.py train [-h] 错误： Using backend: pytorch usage: GBGCN.py train [-h] [-DS DATASET] [-D DEVICE [DEVICE ...]] -T TAG [-SEP SAMPLE_EPOCH] [-SW SAMPLE_WORKER] [-EP EPOCH] [-BS BATCH_SIZE] [-BW BATCH_WORKER] [-TBS TEST_BATCH_SIZE] [-TBW TEST_BATCH_WORKER] [-EB EMBEDDING_SIZE] [--lr LR [LR ...]] --L2 L2 [L2 ...] --SL2 SL2 [SL2 ...] -L LAYER [LAYER ...] -A ALPHA [ALPHA ...] -B BETA [BETA ...] [--act ACT] [--pretrain | --no-pretrain] GBGCN.py train: error: the following arguments are required: -T/--tag, --L2, --SL2, -L/--layer, -A/--alpha, -B/--beta

    opened by Ganoder 2
  • Negative sample files

    Negative sample files

    Hi, My question is how to use negative sample file in order to run the whole model correctly? should I copy the file in BeiBei folder? Can I run the model correctly without "negative sample file"? Any instruction from scratch would be of any help. Thanks

    opened by Ali-khn 2
  • TypeError: metaclass conflict: the metaclass of a derived class must be a (non-strict) subclass of the metaclasses of all its bases

    TypeError: metaclass conflict: the metaclass of a derived class must be a (non-strict) subclass of the metaclasses of all its bases

    作者您好，我安装了requirements.txt和librecframework之后运行GBGCN.py，遇到了以下错误： Traceback (most recent call last): File "GBGCN.py", line 14, in from librecframework.argument.manager import HyperparamManager File "C:\Users\ZSX\AppData\Roaming\Python\Python36\site-packages\librecframework\argument_init_.py", line 11, in class Argument(NamedTuple, Generic[T]): TypeError: metaclass conflict: the metaclass of a derived class must be a (non-strict) subclass of the metaclasses of all its bases

    请问这是什么情况呢

    opened by zanshuxun 2
Owner
Jun Zhang
EE, Tsinghua University
Jun Zhang
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