--- language: - de - en - es - fr - it - ja - ko - nl - pl - pt - zh license: apache-2.0 task_categories: - text-retrieval - sentence-similarity tags: - job-titles - similarity - multilingual - ranking - information-retrieval configs: - config_name: de data_files: - split: queries path: "de/queries-00000-of-00001.parquet" - split: corpus path: "de/corpus-00000-of-00001.parquet" - config_name: en data_files: - split: queries path: "en/queries-00000-of-00001.parquet" - split: corpus path: "en/corpus-00000-of-00001.parquet" - config_name: es data_files: - split: queries path: "es/queries-00000-of-00001.parquet" - split: corpus path: "es/corpus-00000-of-00001.parquet" - config_name: fr data_files: - split: queries path: "fr/queries-00000-of-00001.parquet" - split: corpus path: "fr/corpus-00000-of-00001.parquet" - config_name: it data_files: - split: queries path: "it/queries-00000-of-00001.parquet" - split: corpus path: "it/corpus-00000-of-00001.parquet" - config_name: ja data_files: - split: queries path: "ja/queries-00000-of-00001.parquet" - split: corpus path: "ja/corpus-00000-of-00001.parquet" - config_name: ko data_files: - split: queries path: "ko/queries-00000-of-00001.parquet" - split: corpus path: "ko/corpus-00000-of-00001.parquet" - config_name: nl data_files: - split: queries path: "nl/queries-00000-of-00001.parquet" - split: corpus path: "nl/corpus-00000-of-00001.parquet" - config_name: pl data_files: - split: queries path: "pl/queries-00000-of-00001.parquet" - split: corpus path: "pl/corpus-00000-of-00001.parquet" - config_name: pt data_files: - split: queries path: "pt/queries-00000-of-00001.parquet" - split: corpus path: "pt/corpus-00000-of-00001.parquet" - config_name: zh data_files: - split: queries path: "zh/queries-00000-of-00001.parquet" - split: corpus path: "zh/corpus-00000-of-00001.parquet" --- # Job Title Similarity Benchmark This dataset contains the **Job Title Similarity** benchmark for easy loading with the HuggingFace `datasets` library. ## Dataset Description This benchmark provides **job title similarity** datasets in **11** different languages, including the English evaluation dataset used in the text ranking experiments reported in the paper _"Learning Job Titles Similarity from Noisy Skill Labels"_ by Zbib et al. (2022), as well as the translated datasets for the other languages introduced in _"Combined Unsupervised and Contrastive Learning for Multilingual Job Recommendations"_ by Deniz et al. (2024). ### Task Overview The task involves ranking a set of job titles, given another job title as query, such that the resulting ranking reflects the semantic similarity of each job title to the query. This requires identifying the most relevant job titles based on their semantic similarity to a given query. ### English Dataset Creation The English dataset was built by starting with 2,724 job titles (short text phrases with the name of an occupation). Next, a minimal pre-processing step with light clean up was applied. The job titles were randomly divided into two groups: - 105 job titles were used as queries - The remaining job titles were used as corpus documents Each query/document pair was labeled for binary relevance after adjudicating two independent human annotations. (The inter-annotator agreement for this binary relevance labels was 86%.) ### Translated Datasets The translated datasets in 10 additional languages replicate the English dataset using Human Translation (HT) or Machine Translation (MT). **Original repository:** [https://github.com/Avature/job-title-similarity](https://github.com/Avature/job-title-similarity) ## Dataset Structure Each subset (configuration) contains two splits: - **`queries`**: Query job titles with their relevant corpus element indices - **`corpus`**: Corpus job titles ### Schema **queries split:** | Column | Type | Description | |--------|------|-------------| | `text` | `string` | The query job title | | `labels` | `list[int]` | Indices of relevant corpus job titles | **corpus split:** | Column | Type | Description | |--------|------|-------------| | `text` | `string` | The corpus job title | ## Usage ```python from datasets import load_dataset # Load a specific subset ds = load_dataset("Avature/Job-Title-Similarity", "en") # Access the data query_surface_forms = ds["queries"]["text"] corpus_surface_forms = ds["corpus"]["text"] label_lists = ds["queries"]["labels"] # Example: Get relevant corpus texts for the first query query_idx = 0 print(f"Query: {query_surface_forms[query_idx]}") print(f"Similar job titles:") for corpus_idx in label_lists[query_idx]: print(f" - {corpus_surface_forms[corpus_idx]}") ``` ## Available Subsets | Subset | Language | Translation | Queries | Corpus | Annotations | |--------|----------|-------------|---------|--------|-------------| | `en` | English | - | 105 | 2,619 | 2,420 | | `de` | German | HT | 104 | 2,529 | 2,342 | | `es` | Spanish | MT | 104 | 2,568 | 2,378 | | `fr` | French | HT | 104 | 2,488 | 2,299 | | `it` | Italian | MT | 104 | 2,528 | 2,344 | | `ja` | Japanese | HT | 104 | 2,553 | 2,352 | | `ko` | Korean | MT | 104 | 2,542 | 2,345 | | `nl` | Dutch | MT | 105 | 2,538 | 2,361 | | `pl` | Polish | MT | 105 | 2,513 | 2,335 | | `pt` | Portuguese | MT | 104 | 2,523 | 2,331 | | `zh` | Chinese | HT | 103 | 2,513 | 2,319 | **Translation key:** HT = Human Translation, MT = Machine Translation ## Citation If you use this dataset, please cite the original papers: ```bibtex @article{zbib2022Learning, title={{Learning Job Titles Similarity from Noisy Skill Labels}}, author={Rabih Zbib and Lucas Alvarez Lacasa and Federico Retyk and Rus Poves and Juan Aizpuru and Hermenegildo Fabregat and Vaidotas Šimkus and Emilia García-Casademont}, journal={{FEAST, ECML-PKDD 2022 Workshop}}, year={{2022}}, url="https://feast-ecmlpkdd.github.io/archive/2022/papers/FEAST2022_paper_4972.pdf" } @inproceedings{deniz2024Combined, title = {Combined Unsupervised and Contrastive Learning for Multilingual Job Recommendations}, author = {Daniel Deniz and Federico Retyk and Laura García-Sardiña and Hermenegildo Fabregat and Luis Gasco and Rabih Zbib}, booktitle = {Proceedings of the 4th Workshop on Recommender Systems for Human Resources (RecSys in {HR} 2024), in conjunction with the 18th {ACM} Conference on Recommender Systems}, year = {2024}, } ``` ## License This dataset is licensed under the Apache 2.0 License. See the [LICENSE](https://github.com/Avature/jobtitlesimilarity-dataset/blob/main/LICENSE) file for more information.