{ "id": 497468, "title": "Starter materials and references ", "url": "/competitions/uspto-explainable-ai/discussion/497468", "author_name": "", "post_date": "2024-04-24T19:28:52.367953400Z", "votes": 10, "comment_count": 2, "views": 0, "content": "

Hello everyone,

\n

Wishing you all the best for the competition. Hope the below materials help one and all onboard effectively-

\n

Competition metric details

\n
    \n
  1. https://labelyourdata.com/articles/mean-average-precision-map#:~:text=In%20computer%20vision%2C%20mean%20average,predictions%20match%20the%20ground%20truth.
    2. \n
  2. https://www.v7labs.com/blog/mean-average-precision
    3. \n
  3. https://kili-technology.com/data-labeling/machine-learning/mean-average-precision-map-a-complete-guide
    4. \n
  4. https://xailient.com/blog/what-is-mean-average-precision-and-how-does-it-work/
    5. \n
  5. https://jonathan-hui.medium.com/map-mean-average-precision-for-object-detection-45c121a31173
    6. \n
\n

Some reading materials on the domain and topics covered

\n
    \n
  1. https://onlinelibrary.wiley.com/doi/abs/10.1002/smj.2699
    2. \n
  2. https://journals.sagepub.com/doi/abs/10.1177/0165551513494641
    3. \n
  3. https://aclanthology.org/W03-2001.pdf
    4. \n
  4. https://ieeexplore.ieee.org/abstract/document/6705231/
    5. \n
  5. https://link.springer.com/chapter/10.1007/978-3-642-33492-4_24
    6. \n
  6. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0212103
    7. \n
  7. https://arxiv.org/abs/2401.06782
    8. \n
  8. https://www.sciencedirect.com/science/article/pii/S1877705815043295
    9. \n
  9. https://www.sciencedirect.com/science/article/abs/pii/S0306457306002044
    10. \n
  10. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=0e3a94e95b5db25906b8f7eedc609117a9e45554
    11. \n
\n

Similar Kaggle assignment references

\n

U.S. Patent Phrase to Phrase Matching

\n

Most voted kernels

\n
    \n
  1. https://www.kaggle.com/code/jhoward/getting-started-with-nlp-for-absolute-beginners
    2. \n
  2. https://www.kaggle.com/code/jhoward/iterate-like-a-grandmaster
    3. \n
  3. https://www.kaggle.com/code/yasufuminakama/pppm-deberta-v3-large-baseline-w-w-b-train
    4. \n
  4. https://www.kaggle.com/code/yasufuminakama/pppm-deberta-v3-large-baseline-inference
    5. \n
  5. https://www.kaggle.com/code/remekkinas/eda-and-feature-engineering
    6. \n
  6. https://www.kaggle.com/code/ksork6s4/uspppm-bert-for-patents-baseline-inference
    7. \n
\n

Good public scores

\n
    \n
  1. https://www.kaggle.com/code/renxingkai/pppm-stacking-10-models
    2. \n
  2. https://www.kaggle.com/code/goldenlock/usp-base
    3. \n
  3. https://www.kaggle.com/code/zzy990106/upppm-ensemble-two-stage-final
    4. \n
  4. https://www.kaggle.com/code/masakiaota/8th-place-solution-infer
    5. \n
  5. https://www.kaggle.com/code/calpis10000/pppm-ens-063
    6. \n
\n

Discussion topics and high scoring writeups

\n
    \n
  1. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332243 -- rank1
    2. \n
  2. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332234 -- rank2
    3. \n
  3. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332420 -- rank3
    4. \n
  4. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332418 -- rank5
    5. \n
  5. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332928 -- rank7
    6. \n
  6. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332492 -- rank8
    7. \n
  7. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332273 -- rank10
    8. \n
  8. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332567 -- rank11
    9. \n
\n

Wishing you all the best for the competition! Happy learning and regards!

", "messages": [ { "id": "2773555", "postDate": "04/24/2024 19:28:52", "content": "

Hello everyone,

\n

Wishing you all the best for the competition. Hope the below materials help one and all onboard effectively-

\n

Competition metric details

\n
    \n
  1. https://labelyourdata.com/articles/mean-average-precision-map#:~:text=In%20computer%20vision%2C%20mean%20average,predictions%20match%20the%20ground%20truth.
    2. \n
  2. https://www.v7labs.com/blog/mean-average-precision
    3. \n
  3. https://kili-technology.com/data-labeling/machine-learning/mean-average-precision-map-a-complete-guide
    4. \n
  4. https://xailient.com/blog/what-is-mean-average-precision-and-how-does-it-work/
    5. \n
  5. https://jonathan-hui.medium.com/map-mean-average-precision-for-object-detection-45c121a31173
    6. \n
\n

Some reading materials on the domain and topics covered

\n
    \n
  1. https://onlinelibrary.wiley.com/doi/abs/10.1002/smj.2699
    2. \n
  2. https://journals.sagepub.com/doi/abs/10.1177/0165551513494641
    3. \n
  3. https://aclanthology.org/W03-2001.pdf
    4. \n
  4. https://ieeexplore.ieee.org/abstract/document/6705231/
    5. \n
  5. https://link.springer.com/chapter/10.1007/978-3-642-33492-4_24
    6. \n
  6. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0212103
    7. \n
  7. https://arxiv.org/abs/2401.06782
    8. \n
  8. https://www.sciencedirect.com/science/article/pii/S1877705815043295
    9. \n
  9. https://www.sciencedirect.com/science/article/abs/pii/S0306457306002044
    10. \n
  10. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=0e3a94e95b5db25906b8f7eedc609117a9e45554
    11. \n
\n

Similar Kaggle assignment references

\n

U.S. Patent Phrase to Phrase Matching

\n

Most voted kernels

\n
    \n
  1. https://www.kaggle.com/code/jhoward/getting-started-with-nlp-for-absolute-beginners
    2. \n
  2. https://www.kaggle.com/code/jhoward/iterate-like-a-grandmaster
    3. \n
  3. https://www.kaggle.com/code/yasufuminakama/pppm-deberta-v3-large-baseline-w-w-b-train
    4. \n
  4. https://www.kaggle.com/code/yasufuminakama/pppm-deberta-v3-large-baseline-inference
    5. \n
  5. https://www.kaggle.com/code/remekkinas/eda-and-feature-engineering
    6. \n
  6. https://www.kaggle.com/code/ksork6s4/uspppm-bert-for-patents-baseline-inference
    7. \n
\n

Good public scores

\n
    \n
  1. https://www.kaggle.com/code/renxingkai/pppm-stacking-10-models
    2. \n
  2. https://www.kaggle.com/code/goldenlock/usp-base
    3. \n
  3. https://www.kaggle.com/code/zzy990106/upppm-ensemble-two-stage-final
    4. \n
  4. https://www.kaggle.com/code/masakiaota/8th-place-solution-infer
    5. \n
  5. https://www.kaggle.com/code/calpis10000/pppm-ens-063
    6. \n
\n

Discussion topics and high scoring writeups

\n
    \n
  1. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332243 -- rank1
    2. \n
  2. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332234 -- rank2
    3. \n
  3. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332420 -- rank3
    4. \n
  4. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332418 -- rank5
    5. \n
  5. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332928 -- rank7
    6. \n
  6. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332492 -- rank8
    7. \n
  7. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332273 -- rank10
    8. \n
  8. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332567 -- rank11
    9. \n
\n

Wishing you all the best for the competition! Happy learning and regards!

", "rawMarkdown": "Hello everyone,\n\nWishing you all the best for the competition. Hope the below materials help one and all onboard effectively-\n\n# Competition metric details\n1. https://labelyourdata.com/articles/mean-average-precision-map#:~:text=In%20computer%20vision%2C%20mean%20average,predictions%20match%20the%20ground%20truth.\n2. https://www.v7labs.com/blog/mean-average-precision\n3. https://kili-technology.com/data-labeling/machine-learning/mean-average-precision-map-a-complete-guide\n4. https://xailient.com/blog/what-is-mean-average-precision-and-how-does-it-work/\n5. https://jonathan-hui.medium.com/map-mean-average-precision-for-object-detection-45c121a31173\n\n# Some reading materials on the domain and topics covered \n1. https://onlinelibrary.wiley.com/doi/abs/10.1002/smj.2699\n2. https://journals.sagepub.com/doi/abs/10.1177/0165551513494641\n3. https://aclanthology.org/W03-2001.pdf\n4. https://ieeexplore.ieee.org/abstract/document/6705231/\n5. https://link.springer.com/chapter/10.1007/978-3-642-33492-4_24\n6. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0212103\n7. https://arxiv.org/abs/2401.06782\n8. https://www.sciencedirect.com/science/article/pii/S1877705815043295\n9. https://www.sciencedirect.com/science/article/abs/pii/S0306457306002044\n10. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=0e3a94e95b5db25906b8f7eedc609117a9e45554\n\n# Similar Kaggle assignment references\n## [U.S. Patent Phrase to Phrase Matching](https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching)\n### Most voted kernels \n1. https://www.kaggle.com/code/jhoward/getting-started-with-nlp-for-absolute-beginners\n2. https://www.kaggle.com/code/jhoward/iterate-like-a-grandmaster\n3. https://www.kaggle.com/code/yasufuminakama/pppm-deberta-v3-large-baseline-w-w-b-train\n4. https://www.kaggle.com/code/yasufuminakama/pppm-deberta-v3-large-baseline-inference\n5. https://www.kaggle.com/code/remekkinas/eda-and-feature-engineering\n6. https://www.kaggle.com/code/ksork6s4/uspppm-bert-for-patents-baseline-inference\n\n### Good public scores \n1. https://www.kaggle.com/code/renxingkai/pppm-stacking-10-models\n2. https://www.kaggle.com/code/goldenlock/usp-base\n3. https://www.kaggle.com/code/zzy990106/upppm-ensemble-two-stage-final\n4. https://www.kaggle.com/code/masakiaota/8th-place-solution-infer\n5. https://www.kaggle.com/code/calpis10000/pppm-ens-063\n\n### Discussion topics and high scoring writeups\n1. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332243 -- rank1\n2. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332234 -- rank2\n3. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332420 -- rank3\n4. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332418 -- rank5\n5. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332928 -- rank7\n6. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332492 -- rank8\n7. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332273 -- rank10\n8. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332567 -- rank11\n\nWishing you all the best for the competition! Happy learning and regards!", "votes": null }, { "id": "2776611", "postDate": "04/26/2024 08:52:28", "content": "

US Patent Phrase to Phrase Matching was my first competition … time really flies!
\nThanks for collecting these resources!

", "rawMarkdown": "US Patent Phrase to Phrase Matching was my first competition ... time really flies!\nThanks for collecting these resources!", "votes": null }, { "id": "2777767", "postDate": "04/26/2024 19:45:03", "content": "

You have come a long way from there, your journey has been nothing less than incredible @valentinwerner

", "rawMarkdown": "You have come a long way from there, your journey has been nothing less than incredible @valentinwerner", "votes": null } ], "comments": [ { "id": 2776611, "author_name": "valentinwerner", "author_url": "", "post_date": "04/26/2024 08:52:28", "content": "

US Patent Phrase to Phrase Matching was my first competition … time really flies!
\nThanks for collecting these resources!

", "votes": null, "replies": [ { "id": 2777767, "author_name": "ravi20076", "author_url": "", "post_date": "04/26/2024 19:45:03", "content": "

You have come a long way from there, your journey has been nothing less than incredible @valentinwerner

", "votes": null, "replies": [] } ] } ], "raw_markdown_by_id": { "2773555": "Hello everyone,\n\nWishing you all the best for the competition. Hope the below materials help one and all onboard effectively-\n\n# Competition metric details\n1. https://labelyourdata.com/articles/mean-average-precision-map#:~:text=In%20computer%20vision%2C%20mean%20average,predictions%20match%20the%20ground%20truth.\n2. https://www.v7labs.com/blog/mean-average-precision\n3. https://kili-technology.com/data-labeling/machine-learning/mean-average-precision-map-a-complete-guide\n4. https://xailient.com/blog/what-is-mean-average-precision-and-how-does-it-work/\n5. https://jonathan-hui.medium.com/map-mean-average-precision-for-object-detection-45c121a31173\n\n# Some reading materials on the domain and topics covered \n1. https://onlinelibrary.wiley.com/doi/abs/10.1002/smj.2699\n2. https://journals.sagepub.com/doi/abs/10.1177/0165551513494641\n3. https://aclanthology.org/W03-2001.pdf\n4. https://ieeexplore.ieee.org/abstract/document/6705231/\n5. https://link.springer.com/chapter/10.1007/978-3-642-33492-4_24\n6. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0212103\n7. https://arxiv.org/abs/2401.06782\n8. https://www.sciencedirect.com/science/article/pii/S1877705815043295\n9. https://www.sciencedirect.com/science/article/abs/pii/S0306457306002044\n10. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=0e3a94e95b5db25906b8f7eedc609117a9e45554\n\n# Similar Kaggle assignment references\n## [U.S. Patent Phrase to Phrase Matching](https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching)\n### Most voted kernels \n1. https://www.kaggle.com/code/jhoward/getting-started-with-nlp-for-absolute-beginners\n2. https://www.kaggle.com/code/jhoward/iterate-like-a-grandmaster\n3. https://www.kaggle.com/code/yasufuminakama/pppm-deberta-v3-large-baseline-w-w-b-train\n4. https://www.kaggle.com/code/yasufuminakama/pppm-deberta-v3-large-baseline-inference\n5. https://www.kaggle.com/code/remekkinas/eda-and-feature-engineering\n6. https://www.kaggle.com/code/ksork6s4/uspppm-bert-for-patents-baseline-inference\n\n### Good public scores \n1. https://www.kaggle.com/code/renxingkai/pppm-stacking-10-models\n2. https://www.kaggle.com/code/goldenlock/usp-base\n3. https://www.kaggle.com/code/zzy990106/upppm-ensemble-two-stage-final\n4. https://www.kaggle.com/code/masakiaota/8th-place-solution-infer\n5. https://www.kaggle.com/code/calpis10000/pppm-ens-063\n\n### Discussion topics and high scoring writeups\n1. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332243 -- rank1\n2. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332234 -- rank2\n3. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332420 -- rank3\n4. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332418 -- rank5\n5. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332928 -- rank7\n6. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332492 -- rank8\n7. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332273 -- rank10\n8. https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching/discussion/332567 -- rank11\n\nWishing you all the best for the competition! Happy learning and regards!", "2776611": "US Patent Phrase to Phrase Matching was my first competition ... time really flies!\nThanks for collecting these resources!", "2777767": "You have come a long way from there, your journey has been nothing less than incredible @valentinwerner" }, "source": "meta" }