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OntoStreamLearn

This space contains some codes and data for our work on ontology stream reasoning and leanring.

  1. predictive_reasoning/: "Learning from ontology streams with semantic concept drift" (IJCAI-17), Chen, Jiaoyan, Freddy Lécué, Jeff Pan, and Huajun Chen.

  2. KBPA_StockPrediction/: "Deep Learning for Knowledge-Driven Ontology Stream Prediction." (CCKS-18), Deng, Shumin, Jeff Z. Pan, Jiaoyan Chen, and Huajun Chen.

  3. WBOE_predictive_reasoning/: "Concept Drift in Ontology Streams? Embedding Semantics for Representation Learning" (Journal of Web Semantics, 2019), Chen, Jiaoyan, Freddy Lécué, Jeff Pan, Chen Huajun and Deng, Shumin (under revision).

Air quality and meteology data

Air quality and meteology data (download by https://goo.gl/UXEw9C):

1. Air quality data are stored in DB:Air, Collection:Stations

2. Meteorology data are stored in DB:forecastio, Collection:Beijing 

3. Information of the stations: station_location.csv

Air data and meteorology data are separatedly exported to files with "mongodump -d db_name -o dir" command. You can use "mongorestore -d db_name -o dir/*" commend to separatedly import them into Mongo DB.

Data for KBPA_StockPrediction

1. The Stock Price Data: extracted from the Google Finance API(http://files.statworx.com/sp500.zip).
It contains minutely price records of 500 stocks from S&P 500, ranging from 3rd April to 31th August in 2017. 

2. Background Knowledge of Stocks: It contains correlative companies information of S&P 500 component stocks, which is stored in a knowledge graph, extracted from Wikipedia

3. Real-time Text Data for Stocks: It contains social media data related to S&P 500 index and stocks when the stock market opening.  We have extracted 98617 tweets with respect to S&P 500 index, from 3rd, April, 2017 to 31st, August, 2017.

For details, you can refer to the paper "Deep Learning for Knowledge-Driven Ontology Stream Prediction" (https://link.springer.com/chapter/10.1007/978-981-13-3146-6_5)

Note

The codes have been out of maintenance. Please contact Jiaoyan Chen for any questions or interests.