Source code for cornac.datasets.citeulike

# Copyright 2018 The Cornac Authors. All Rights Reserved.
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"""
This dataset is mostly from the paper 'Collaborative topic modeling for recommending scientific articles'
[Wang and Blei - KDD 2011].  It was further collected, named `citeulike-a`, and used in the paper
'Collaborative Topic Regression with Social Regularization' [Wang, Chen and Li - IJCAI 2013].

Link to the data: http://www.wanghao.in/CDL.htm
"""

from typing import List

from ..utils import cache
from ..data import Reader


[docs]def load_data(reader: Reader = None) -> List: """Load the implicit feedback between users and items Parameters ---------- reader: `obj:cornac.data.Reader`, default: None Reader object used to read the data. Returns ------- data: array-like Data in the form of a list of tuples (user, item, 1). """ fpath = cache(url='https://static.preferred.ai/cornac/datasets/citeulike/users.zip', relative_path='citeulike/users.dat', unzip=True) reader = Reader() if reader is None else reader return reader.read(fpath, fmt='UI', sep=' ', id_inline=True)
[docs]def load_text(): """Load item texts including tile and abstract joined together into one document per item. Returns ------- texts: List List of text documents, one per item. ids: List List of item ids aligned with indices in `texts`. """ import csv texts, ids = [], [] fpath = cache(url='https://static.preferred.ai/cornac/datasets/citeulike/text.zip', relative_path='citeulike/raw-data.csv', unzip=True) with open(fpath, 'r', encoding='utf-8', errors='ignore') as f: next(f) for row in csv.reader(f, delimiter=',', quotechar='"'): ids.append(row[0]) texts.append(row[3] + '. ' + row[4]) return texts, ids