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@@ -52,3 +52,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+assign.json filter=lfs diff=lfs merge=lfs -text
+paper_new.json filter=lfs diff=lfs merge=lfs -text

SciGraph.py

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+# -*- coding: utf-8 -*-
+"""
+@Project    : indexing
+@File       : SciGraph
+@Email      : [email protected]
+@Author     : Yan Yuchen
+@Time       : 2023/3/9 12:53
+"""
+import json
+import datasets
+import pandas as pd
+import numpy as np
+from sklearn.model_selection import train_test_split
+
+
+_CITATION = """\
+@InProceedings{yan-EtAl:2022:Poster,
+  author    = {Yuchen Yan and Chong Chen},
+  title     = {SciGraph: A Knowledge Graph Constructed by Function and Topic Annotation of Scientific Papers},
+  booktitle = {3rd Workshop on Extraction and Evaluation of Knowledge Entities from Scientific Documents (EEKE2022), June 20-24, 2022, Cologne, Germany and Online},
+  month     = {June},
+  year      = {2022},
+  address   = {Beijing, China},
+  url       = {https://ceur-ws.org/Vol-3210/paper16.pdf}
+}
+"""
+
+_DESCRIPTION = """\
+"""
+
+_HOMEPAGE = ""
+
+# The license information was obtained from https://github.com/boudinfl/ake-datasets as the dataset shared over here is taken from here
+_LICENSE = ""
+
+# TODO: Add link to the official dataset URLs here
+
+
+# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
+class SciGraph(datasets.GeneratorBasedBuilder):
+    """TODO: Short description of my dataset."""
+
+    VERSION = datasets.Version("0.0.1")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="function", version=VERSION,
+                               description="This part of my dataset covers extraction"),
+        datasets.BuilderConfig(name="topic", version=VERSION,
+                               description="This part of my dataset covers generation")
+    ]
+    
+    DEFAULT_CONFIG_NAME = "function"
+
+    def _info(self):
+        with open('class.json', 'r') as f:
+            classes = list(json.load(f).keys())
+        if self.config.name == "function":  # This is the name of the configuration selected in BUILDER_CONFIGS above
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "abstract": datasets.Value("string"),
+                    "label": datasets.features.ClassLabel(names=classes, num_classes=len(classes))
+                }
+            )
+        else:
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "abstract": datasets.Value("string"),
+                    "keywords": datasets.features.Sequence(datasets.Value("string"))
+                }
+            )
+
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # This defines the different columns of the dataset and their types
+            features=features,
+            homepage=_HOMEPAGE,
+            # License for the dataset if available
+            license=_LICENSE,
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "split": "test"
+                },
+            )
+        ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, split):
+        if self.config.name == 'function':
+            with open('class.json', 'r') as f:
+                functions = list(json.load(f).keys())
+            data = pd.read_json('assign.json')
+
+            if split == 'train':
+                data = data.loc[data[functions].sum(axis=1) == 1]
+                data['label'] = [functions[row.tolist().index(1)] for index, row in data[functions].iterrows()]
+                data = data[['_id', 'abstract', 'label']]
+                for idx, row in data.iterrows():
+                    yield idx, {
+                        "id": row._id,
+                        "abstract": row.abstract,
+                        "label": row.label
+                    }
+            elif split == 'test':
+                data = data.loc[data[functions].sum(axis=1) == 0]
+                data = data[['_id', 'abstract']]
+                for idx, row in data.iterrows():
+                    yield idx, {
+                        "id": row._id,
+                        "abstract": row.abstract,
+                        "label": -1
+                    }
+
+        if self.config.name == 'topic':
+            data = pd.read_json('paper_new.json')
+            data = data.replace(to_replace=r'^\s*$', value=np.nan, regex=True).dropna(subset=['keywords'], axis=0)
+
+            train_data, test_data = train_test_split(data, test_size=0.1, random_state=42)
+            if split == 'train':
+                for idx, row in train_data.iterrows():
+                    yield idx, {
+                        "id": row._id,
+                        "abstract": row.abstract,
+                        "keywords": row.keywords.split('#%#')
+                    }
+            elif split == 'test':
+                for idx, row in test_data.iterrows():
+                    yield idx, {
+                        "id": row._id,
+                        "abstract": row.abstract,
+                        "keywords": row.keywords.split('#%#')
+                    }

assign.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5ec51303427147a084ede88bc2efebb585bbea5b1f51677548b025611ee2aa95
+size 788137793

class.json

@@ -0,0 +1,8 @@
+{
+  "综述与进展": ["综述", "进展", "现状", "展望", "启示", "趋势", "前景"],
+  "论证与对比": ["说明", "评价", "评估", "分析", "对比", "比较", "改善", "验证", "改进"],
+  "思考与探讨": ["思考", "讨论", "探讨", "意义", "浅谈", "探析", "建议", "探索", "探究"],
+  "原理与计算": ["基础", "计算", "理论", "原理", "求解", "规律", "理念", "性质", "机制"],
+  "技术与方法": ["技术", "方法", "算法", "模型", "思路", "对策", "措施", "策略", "方式"],
+  "设计与应用": ["设计", "实现", "应用", "实践", "方案", "案例", "运用", "制作", "研发", "研制"]
+}

paper_new.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e0236f2328a844ebc7caa7f4209685d55041d9a9621c89d9efc39e8f0653c3ce
+size 885375447