This repository contains scripts and programs used to analyze textual data from the Instagram API in the context of automatic intelligent fashion identification, classification and recommendation.

• ./clean_data contains scripts for converting JSON Instagram data to csv,tsv,reduced json files that are suited for processing
• ./data_exploration contains some descriptive analytics about the data
• ./fasttext_on_spark contains a scalable implementation of FastText to run on Spark clusters
• ./information_extraction contains scripts for unsupervised information extraction using semantic/syntactic clustering of text to match it to an ontology/domain data as well as using several external APIs as sources of distant supervision. Also contains scripts for evaluation.
• ./wordvecs contains scripts training and evaluating word embeddings, as well as normalizing text corpora to be used for training word embeddings.
• ./cnn_classification contains scripts for training a weakly supervised CNN text classifier and model serving.

See individual README.md for each module

If using any of the code in this repsitory in your work or research, please cite: 1

[1] K.Hammar, S.Jaradat, N.Dokoohaki, M.Matskin TODO

@INPROCEEDINGS{8609589,
author={K. Hammar and S. Jaradat and N. Dokoohaki and M. Matskin},
booktitle={2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)},
title={Deep Text Mining of Instagram Data without Strong Supervision},
year={2018},
volume={},
number={},
pages={158-165},
keywords={Twitter;Ontologies;Task analysis;Clothing;Text mining;Information Extraction;Instagram;Weak Supervision;Word Embeddings},
doi={10.1109/WI.2018.00-94},
ISSN={},
month={Dec},}

BSD 2-clause, see LICENSE

Kim Hammar, [email protected]

Shatha Jaradat, [email protected]

Nima Dokoohaki, [email protected]