# Google Scholar — Zapi reference > Pencarian publikasi ilmiah Google Scholar + profil author (sitasi, h-index, daftar publikasi). **Base URL:** `https://api.zpi.web.id` **Auth:** Send `x-api-key: YOUR_KEY` header on every request. Get a free key at https://zpi.web.id/dashboard/keys. **Response envelope:** `{ status, message, content }` **Rate limit:** 60 req/min on free tier. **Related:** - Detail page: https://zpi.web.id/api/research/google-scholar - Endpoint catalog: https://zpi.web.id/category/research - Concise index: https://zpi.web.id/llms.txt - Full reference: https://zpi.web.id/llms-full.txt --- ## Google Scholar **Category:** research · **Slug:** `google-scholar` **Detail page:** https://zpi.web.id/api/research/google-scholar Pencarian publikasi ilmiah Google Scholar + profil author (sitasi, h-index, daftar publikasi). **Tags:** google-scholar, scholar, akademik, jurnal, sitasi, riset, paper ### Cari Publikasi Cari publikasi ilmiah di Google Scholar (filter tahun, bahasa, paten, sitasi). - **Method:** `GET` - **Endpoint:** `https://api.zpi.web.id/v1/research:google-scholar/search` - **Cache TTL:** 3600s **Parameters:** | Name | Type | Location | Required | Description | |------|------|----------|----------|-------------| | `query` | string | query | yes | Academic search keyword. Supports operators like author:, source:, intitle:. | | `page` | number | query | no | Page number (10 results per page). Default 1 | | `yearFrom` | number | query | no | Only include results published from this year | | `yearTo` | number | query | no | Only include results published up to this year | | `language` | string | query | no | Interface language code (hl=). Default en | | `patents` | enum(true|false) | query | no | Include patents in results. Default true | | `citations` | enum(true|false) | query | no | Include citation-only (no fulltext) entries. Default true | **cURL:** ```bash curl "https://api.zpi.web.id/v1/research:google-scholar/search?query=transformer%20neural%20network&page=1&yearFrom=2018&yearTo=2024&language=en&patents=true&citations=true" \ -H "x-api-key: YOUR_API_KEY" ``` **JavaScript / TypeScript:** ```javascript const res = await fetch("https://api.zpi.web.id/v1/research:google-scholar/search?query=transformer%20neural%20network&page=1&yearFrom=2018&yearTo=2024&language=en&patents=true&citations=true", { headers: { "x-api-key": process.env.ZAPI_KEY } }); const data = await res.json(); ``` **Python:** ```python import requests r = requests.get("https://api.zpi.web.id/v1/research:google-scholar/search?query=transformer%20neural%20network&page=1&yearFrom=2018&yearTo=2024&language=en&patents=true&citations=true", headers={"x-api-key": "YOUR_API_KEY"}) data = r.json() ``` **Example response:** ```json { "page": 1, "count": 10, "query": "transformer neural network", "hasMore": true, "perPage": 10, "results": [ { "link": "https://homes.esat.kuleuven.be/~konijn/publications/2021/Liu2.pdf", "type": "PDF", "year": 2021, "title": "Transformer in convolutional neural networks", "venue": "arXiv preprint arXiv", "pdfUrl": "https://homes.esat.kuleuven.be/~konijn/publications/2021/Liu2.pdf", "authors": [ "Y Liu", "G Sun", "Y Qiu", "L Zhang" ], "snippet": "… of totally abandoning them as done in recent transformer works [16–20], we aim at introducing a generic framework that could inherit the advantages of both CNNs and transformers . …", "resultId": "Xhupwy48-swJ", "versions": 0, "publisher": "homes.esat.kuleuven.be", "citedByUrl": "https://scholar.google.com/scholar?cites=14770184099463764830&as_sdt=2005&sciodt=0,5&hl=en", "relatedUrl": "https://scholar.google.com/scholar?q=related:Xhupwy48-swJ:scholar.google.com/&scioq=transformer+neural+network&hl=en&as_sdt=0,5", "citedByCount": 112, "authorProfiles": [ { "name": "Y Liu", "authorId": "UB3doCoAAAAJ" }, { "name": "G Sun", "authorId": "qd8Blw0AAAAJ" }, { "name": "L Zhang", "authorId": "61LOyWUAAAAJ" } ], "publicationInfo": "Y Liu , G Sun , Y Qiu, L Zhang … - arXiv preprint arXiv …, 2021 - homes.esat.kuleuven.be" }, { "link": "https://arxiv.org/abs/1907.05572", "type": "PDF", "year": 2019, "title": "R- transformer : Recurrent neural network enhanced transformer", "venue": "arXiv preprint arXiv", "pdfUrl": "https://arxiv.org/pdf/1907.05572", "authors": [ "Z Wang", "Y Ma", "Z Liu", "J Tang" ], "snippet": "… Unlike previously proposed Transformer -like models, R- Transformer in this work leverages the strength of RNN and is able model the local structures effectively without the need of any …", "resultId": "9jQQcRuE-5gJ", "versions": 4, "publisher": "arxiv.org", "citedByUrl": "https://scholar.google.com/scholar?cites=11023549766315291894&as_sdt=2005&sciodt=0,5&hl=en", "relatedUrl": "https://scholar.google.com/scholar?q=related:9jQQcRuE-5gJ:scholar.google.com/&scioq=transformer+neural+network&hl=en&as_sdt=0,5", "citedByCount": 180, "authorProfiles": [ { "name": "Z Wang", "authorId": "nvNEalYAAAAJ" }, { "name": "Y Ma", "authorId": "wf9TTOIAAAAJ" }, { "name": "Z Liu", "authorId": "rRTzNm0AAAAJ" }, { "name": "J Tang", "authorId": "WtzKMWAAAAAJ" } ], "publicationInfo": "Z Wang , Y Ma , Z Liu , J Tang - arXiv preprint arXiv:1907.05572, 2019 - arxiv.org" }, { "link": "https://www.sciencedirect.com/science/article/pii/S136481522200281X", "type": "", "year": 2023, "title": "Transformer neural networks for interpretable flood forecasting", "venue": "… Modelling & Software", "pdfUrl": "", "authors": [ "M Castangia", "LMM Grajales", "A Aliberti", "C Rossi" ], "snippet": "… the applicability of the Transformer neural network to the task … that the Transformer outperforms recurrent neural networks by … Furthermore, the Transformer requires lower computational …", "resultId": "eaSqVjEELZcJ", "versions": 5, "publisher": "Elsevier", "citedByUrl": "https://scholar.google.com/scholar?cites=10893367683633030265&as_sdt=2005&sciodt=0,5&hl=en", "relatedUrl": "https://scholar.google.com/scholar?q=related:eaSqVjEELZcJ:scholar.google.com/&scioq=transformer+neural+network&hl=en&as_sdt=0,5", "citedByCount": 178, "authorProfiles": [ { "name": "M Castangia", "authorId": "RulBKsMAAAAJ" }, { "name": "A Aliberti", "authorId": "A_EadKUAAAAJ" }, { "name": "C Rossi", "authorId": "Wwyz_joAAAAJ" } ], "publicationInfo": "M Castangia , LMM Grajales, A Aliberti , C Rossi … - … Modelling & Software, 2023 - Elsevier" }, { "link": "https://dl.acm.org/doi/abs/10.1145/3388440.3412467", "type": "PDF", "year": 2020, "title": "Transforming the language of life: transformer neural networks for protein prediction tasks", "venue": "Proceedings of the 11th", "pdfUrl": "https://dl.acm.org/doi/pdf/10.1145/3388440.3412467", "authors": [ "A Nambiar", "M Heflin", "S Liu", "S Maslov" ], "snippet": "… We present a Transformer neural network that pre-trains task-agnostic sequence representations. This model is fine-tuned to solve two different protein prediction tasks: protein family …", "resultId": "fS-AVuwxGuAJ", "versions": 9, "publisher": "dl.acm.org", "citedByUrl": "https://scholar.google.com/scholar?cites=16148274305023618941&as_sdt=2005&sciodt=0,5&hl=en", "relatedUrl": "https://scholar.google.com/scholar?q=related:fS-AVuwxGuAJ:scholar.google.com/&scioq=transformer+neural+network&hl=en&as_sdt=0,5", "citedByCount": 198, "authorProfiles": [ { "name": "A Nambiar", "authorId": "cQZWTbMAAAAJ" }, { "name": "S Liu", "authorId": "ktb2fSwAAAAJ" }, { "name": "S Maslov", "authorId": "TOkEuagAAAAJ" } ], "publicationInfo": "A Nambiar , M Heflin, S Liu , S Maslov … - Proceedings of the 11th …, 2020 - dl.acm.org" }, { "link": "https://aclanthology.org/C18-1054/", "type": "PDF", "year": 2018, "title": "A comparison of transformer and recurrent neural networks on multilingual neural machine translation", "venue": "Proceedings of the 27th", "pdfUrl": "https://aclanthology.org/C18-1054.pdf", "authors": [ "SM Lakew", "M Cettolo", "M Federico" ], "snippet": "… investigates the translation quality of two of the currently dominant neural architectures in MT, which are the Recurrent and the Transformer ones; and (iii) quantitatively explores how the …", "resultId": "J8p83ayKPy8J", "versions": 8, "publisher": "aclanthology.org", "citedByUrl": "https://scholar.google.com/scholar?cites=3404592318370335271&as_sdt=2005&sciodt=0,5&hl=en", "relatedUrl": "https://scholar.google.com/scholar?q=related:J8p83ayKPy8J:scholar.google.com/&scioq=transformer+neural+network&hl=en&as_sdt=0,5", "citedByCount": 210, "authorProfiles": [ { "name": "SM Lakew", "authorId": "GEB4LhgAAAAJ" }, { "name": "M Cettolo", "authorId": "5uWajM4AAAAJ" }, { "name": "M Federico", "authorId": "WaGw_qYAAAAJ" } ], "publicationInfo": "SM Lakew , M Cettolo , M Federico - Proceedings of the 27th …, 2018 - aclanthology.org" }, { "link": "https://arxiv.org/abs/2209.15425", "type": "PDF", "year": 2022, "title": "Spikformer: When spiking neural network meets transformer", "venue": "arXiv preprint arXiv", "pdfUrl": "https://arxiv.org/pdf/2209.15425", "authors": [ "Z Zhou", "Y Zhu", "C He", "Y Wang", "S Yan", "Y Tian" ], "snippet": "… We propose Spiking Transformer (Spikformer), which incorporates the self-attention mechanism and Transformer into the spiking neural networks (SNNs) for enhanced learning …", "resultId": "YBqrsf24cakJ", "versions": 4, "publisher": "arxiv.org", "citedByUrl": "https://scholar.google.com/scholar?cites=12209743464525142624&as_sdt=2005&sciodt=0,5&hl=en", "relatedUrl": "https://scholar.google.com/scholar?q=related:YBqrsf24cakJ:scholar.google.com/&scioq=transformer+neural+network&hl=en&as_sdt=0,5", "citedByCount": 684, "authorProfiles": [ { "name": "Z Zhou", "authorId": "4nz-h1QAAAAJ" }, { "name": "Y Zhu", "authorId": "HBp_nuAAAAAJ" }, { "name": "Y Wang", "authorId": "o_DllmIAAAAJ" }, { "name": "S Yan", "authorId": "DNuiPHwAAAAJ" }, { "name": "Y Tian", "authorId": "fn6hJx0AAAAJ" } ], "publicationInfo": "Z Zhou , Y Zhu , C He, Y Wang , S Yan , Y Tian … - arXiv preprint arXiv …, 2022 - arxiv.org" }, { "link": "https://ieeexplore.ieee.org/abstract/document/544265/", "type": "PDF", "year": 1996, "title": "An artificial neural network approach to transformer fault diagnosis", "venue": "IEEE transactions on power", "pdfUrl": "https://vtechworks.lib.vt.edu/bitstreams/9bce9f02-3dc2-4b68-914f-9576c7a6800a/download", "authors": [ "Y Zhang", "X Ding", "Y Liu", "PJ Griffin" ], "snippet": "… This paper presents an artificial neural network (ANN) approach to diagnose and detect faults in oil-filled power transformers based on dissolved gas-in-oil analysis. A twostep ANN …", "resultId": "BpubS3GIt-UJ", "versions": 12, "publisher": "ieeexplore.ieee.org", "citedByUrl": "https://scholar.google.com/scholar?cites=16552848975604718342&as_sdt=2005&sciodt=0,5&hl=en", "relatedUrl": "https://scholar.google.com/scholar?q=related:BpubS3GIt-UJ:scholar.google.com/&scioq=transformer+neural+network&hl=en&as_sdt=0,5", "citedByCount": 612, "authorProfiles": [ { "name": "Y Liu", "authorId": "qHDlIS8AAAAJ" } ], "publicationInfo": "Y Zhang, X Ding, Y Liu , PJ Griffin - IEEE transactions on power …, 1996 - ieeexplore.ieee.org" }, { "link": "https://www.mdpi.com/2076-3417/13/9/5521", "type": "HTML", "year": 2023, "title": "Comparing vision transformers and convolutional neural networks for image classification: A literature review", "venue": "Applied Sciences", "pdfUrl": "https://www.mdpi.com/2076-3417/13/9/5521", "authors": [ "J Maurício", "I Domingues", "J Bernardino" ], "snippet": "… Transformers are models that implement a mechanism of self… Neural Networks for image classification and transformers … Transformers (ViT) and Convolutional Neural Networks . The …", "resultId": "3RtgwJzWuNwJ", "versions": 10, "publisher": "mdpi.com", "citedByUrl": "https://scholar.google.com/scholar?cites=15904698052789672925&as_sdt=2005&sciodt=0,5&hl=en", "relatedUrl": "https://scholar.google.com/scholar?q=related:3RtgwJzWuNwJ:scholar.google.com/&scioq=transformer+neural+network&hl=en&as_sdt=0,5", "citedByCount": 797, "authorProfiles": [ { "name": "J Maurício", "authorId": "qkfnuSAAAAAJ" }, { "name": "I Domingues", "authorId": "wsX09lEAAAAJ" }, { "name": "J Bernardino", "authorId": "EpJW32AAAAAJ" } ], "publicationInfo": "J Maurício , I Domingues , J Bernardino - Applied Sciences, 2023 - mdpi.com" } ], "nextPage": 2, "didYouMean": null, "totalResults": null } ``` --- ### Profil Author Profil author Google Scholar — metrik sitasi, h-index, i10, dan daftar publikasi. - **Method:** `GET` - **Endpoint:** `https://api.zpi.web.id/v1/research:google-scholar/author` - **Cache TTL:** 3600s **Parameters:** | Name | Type | Location | Required | Description | |------|------|----------|----------|-------------| | `userId` | string | query | yes | Author profile ID (the `user` param from a profile URL; also returned as `authorProfiles[].authorId` by the search endpoint). | | `page` | number | query | no | Publications page (100 per page). Default 1 | | `sortBy` | enum(cited|year) | query | no | Sort publications by citation count or year. Default cited | | `language` | string | query | no | Interface language (hl=). Default en | **cURL:** ```bash curl "https://api.zpi.web.id/v1/research:google-scholar/author?userId=UB3doCoAAAAJ&page=1&sortBy=cited&language=en" \ -H "x-api-key: YOUR_API_KEY" ``` **JavaScript / TypeScript:** ```javascript const res = await fetch("https://api.zpi.web.id/v1/research:google-scholar/author?userId=UB3doCoAAAAJ&page=1&sortBy=cited&language=en", { headers: { "x-api-key": process.env.ZAPI_KEY } }); const data = await res.json(); ``` **Python:** ```python import requests r = requests.get("https://api.zpi.web.id/v1/research:google-scholar/author?userId=UB3doCoAAAAJ&page=1&sortBy=cited&language=en", headers={"x-api-key": "YOUR_API_KEY"}) data = r.json() ``` **Example response:** ```json { "name": "Yun Liu", "page": 1, "photo": null, "userId": "UB3doCoAAAAJ", "hasMore": false, "metrics": { "hIndexAll": 43, "i10IndexAll": 60, "citationsAll": 12299, "hIndexRecent": 41, "i10IndexRecent": 58, "citationsRecent": 10871 }, "perPage": 100, "interests": [ "Computer Vision" ], "affiliation": "Professor of Computer Science, Nankai University", "emailDomain": "nankai.edu.cn", "publications": [ { "url": "https://scholar.google.com/citations?view_op=view_citation&hl=en&user=UB3doCoAAAAJ&pagesize=100&citation_for_view=UB3doCoAAAAJ:l7t_Zn2s7bgC", "year": 2017, "title": "Structure-measure: A New Way to Evaluate Foreground Maps", "venue": "IEEE International Conference on Computer Vision", "authors": "DP Fan, MM Cheng, Y Liu, T Li, A Borji", "citationId": "UB3doCoAAAAJ:l7t_Zn2s7bgC", "citedByCount": 2486 }, { "url": "https://scholar.google.com/citations?view_op=view_citation&hl=en&user=UB3doCoAAAAJ&pagesize=100&citation_for_view=UB3doCoAAAAJ:dQ2og3OwTAUC", "year": 2019, "title": "Richer Convolutional Features for Edge Detection", "venue": "IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE CVPR 2017)", "authors": "Y Liu, MM Cheng, X Hu, JW Bian, L Zhang, X Bai, J Tang", "citationId": "UB3doCoAAAAJ:dQ2og3OwTAUC", "citedByCount": 1638 }, { "url": "https://scholar.google.com/citations?view_op=view_citation&hl=en&user=UB3doCoAAAAJ&pagesize=100&citation_for_view=UB3doCoAAAAJ:GtLg2Ama23sC", "year": 2020, "title": "MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation", "venue": "IEEE Transactions on Pattern Analysis and Machine Intelligence", "authors": "S Li, YA Farha, Y Liu, MM Cheng, J Gall", "citationId": "UB3doCoAAAAJ:GtLg2Ama23sC", "citedByCount": 1251 }, { "url": "https://scholar.google.com/citations?view_op=view_citation&hl=en&user=UB3doCoAAAAJ&pagesize=100&citation_for_view=UB3doCoAAAAJ:W5xh706n7nkC", "year": 2020, "title": "GMS: Grid-based Motion Statistics for Fast, Ultra-robust Feature Correspondence", "venue": "International Journal of Computer Vision", "authors": "JW Bian, WY Lin, Y Liu, L Zhang, SK Yeung, MM Cheng, I Reid", "citationId": "UB3doCoAAAAJ:W5xh706n7nkC", "citedByCount": 962 }, { "url": "https://scholar.google.com/citations?view_op=view_citation&hl=en&user=UB3doCoAAAAJ&pagesize=100&citation_for_view=UB3doCoAAAAJ:e_rmSamDkqQC", "year": 2022, "title": "P2T: Pyramid Pooling Transformer for Scene Understanding", "venue": "IEEE Transactions on Pattern Analysis and Machine Intelligence", "authors": "YH Wu#, Y Liu#, X Zhan, MM Cheng", "citationId": "UB3doCoAAAAJ:e_rmSamDkqQC", "citedByCount": 406 }, { "url": "https://scholar.google.com/citations?view_op=view_citation&hl=en&user=UB3doCoAAAAJ&pagesize=100&citation_for_view=UB3doCoAAAAJ:zLWjf1WUPmwC", "year": 2022, "title": "EDN: Salient Object Detection via Extremely-Downsampled Network", "venue": "IEEE Transactions on Image Processing", "authors": "YH Wu#, Y Liu#, L Zhang, MM Cheng, B Ren", "citationId": "UB3doCoAAAAJ:zLWjf1WUPmwC", "citedByCount": 349 }, { "url": "https://scholar.google.com/citations?view_op=view_citation&hl=en&user=UB3doCoAAAAJ&pagesize=100&citation_for_view=UB3doCoAAAAJ:VOx2b1Wkg3QC", "year": 2018, "title": "Crowd Counting With Deep Negative Correlation Learning", "venue": "IEEE Conference on Computer Vision and Pattern Recognition", "authors": "Z Shi, L Zhang, Y Liu, X Cao, Y Ye, MM Cheng, G Zheng", "citationId": "UB3doCoAAAAJ:VOx2b1Wkg3QC", "citedByCount": 326 }, { "url": "https://scholar.google.com/citations?view_op=view_citation&hl=en&user=UB3doCoAAAAJ&pagesize=100&citation_for_view=UB3doCoAAAAJ:Ug5p-4gJ2f0C", "year": 2023, "title": "LSDIR Dataset: A Large Scale Dataset for Image Restoration", "venue": "IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1775-1787", "authors": "Y Li, K Zhang, J Liang, J Cao, C Liu, R Gong, Y Zhang, H Tang, Y Liu, ...", "citationId": "UB3doCoAAAAJ:Ug5p-4gJ2f0C", "citedByCount": 307 } ], "publicationCount": 90 } ``` --- _Generated: 2026-08-02T14:25:28.119Z_