SE-PQA: a Resource for Personalized Community Question Answering

DOI10.5281/zenodo.10679181Zenodo10679181MaRDI QIDQ6718488

Dataset published at Zenodo repository.

Author name not available (Why is that?)

Publication date: 16 May 2023

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Description

Personalization in Information Retrieval is a topic studied for a long time. Nevertheless, there is still a lack of high-quality, real-world datasets to conduct large-scale experiments and evaluate models for personalized search. This paper contributes to fill this gap by introducing SE-PQA (StackExchange - Personalized Question Answering), a new resource to design and evaluate personalized models related to the two tasks of community Question Answering (cQA). The contributed dataset includes more than 1 million queries and 2 million answers, annotated with a rich set of features modeling the social interactions among the users of a popular cQA platform. We describe the characteristics of SE-PQA and detail the features associated with both questions and answers. We also provide reproducible baseline methods for the cQA task based on the resource, including deep learning models and personalization approaches. The results of the preliminary experiments conducted show the appropriateness of SE-PQA to train effective cQA models; they also show that personalization improves remarkably the effectiveness of all the methods tested. Furthermore, we show the benefits in terms of robustness and generalization of combining data from multiple communities for personalization purposes. Performance on all communities separately: Community Model (BM25 +) P@1 NDCG@3 NDCG@10 R@100 MAP@100 $\lambda$ Academia MiniLM 0.438 0.382 0.395 0.489 0.344 (.1,.9) MiniLM + TAG 0.453 0.392 0.403 0.489 0.352 (.1,.8,.1) Anime MiniLM + TAG 0.650 0.682 0.714 0.856 0.683 (.1,.9,.0) Apple MiniLM 0.327 0.351 0.381 0.514 0.349 (.1,.9) MiniLM + TAG 0.335 0.361 0.389 0.514 0.357 (.1,.8,.1) Bicycles MiniLM 0.405 0.380 0.421 0.600 0.365 (.1,.9) MiniLM + TAG 0.436 0.405 0.441 0.600 0.386 (.1,.8,.1) Boardgames MiniLM 0.681 0.694 0.728 0.866 0.692 (.1,.9) MiniLM + TAG 0.696 0.702 0.736 0.866 0.699 (.1,.8,.1) Buddhism MiniLM + TAG 0.490 0.387 0.397 0.544 0.334 (.3,.7,.0) Christianity MiniLM 0.534 0.505 0.555 0.783 0.497 (.2,.8) MiniLM + TAG 0.549 0.521 0.564 0.783 0.507 (.1,.8,.1) Cooking MiniLM 0.600 0.567 0.600 0.719 0.553 (.1,.9) MiniLM + TAG 0.619 0.583 0.614 0.719 0.568 (.1,.8,.1) DIY MiniLM 0.323 0.313 0.346 0.501 0.302 (.1,.9) MiniLM + TAG 0.335 0.324 0.356 0.501 0.312 (.1,.8,.1) Expatriates MiniLM + TAG 0.596 0.653 0.682 0.832 0.645 (.1,.9,.0) Fitness MiniLM + TAG 0.568 0.575 0.613 0.760 0.567 (.2,.8,.0) Freelancing MiniLM + TAG 0.513 0.472 0.506 0.654 0.457 (.1,.9,.0) Gaming MiniLM 0.510 0.534 0.562 0.686 0.532 (.1,.9) MiniLM + TAG 0.519 0.547 0.571 0.686 0.541 (.1,.8,.1) Gardening MiniLM 0.344 0.362 0.396 0.520 0.359 (.1,.9) MiniLM + TAG 0.345 0.369 0.399 0.520 0.363 (.1,.8,.1) Genealogy MiniLM + TAG 0.592 0.605 0.631 0.779 0.594 (.3,.7,.0) Health MiniLM + TAG 0.718 0.765 0.797 0.934 0.765 (.2,.8,.0) Gaming MiniLM 0.510 0.534 0.562 0.686 0.532 (.1,.9) MiniLM + TAG 0.519 0.547 0.571 0.686 0.541 (.1,.8,.1) Hermeneutics MiniLM 0.589 0.538 0.593 0.828 0.526 (.2,.8) MiniLM + TAG 0.632 0.570 0.617 0.828 0.552 (.1,.8,.1) Hinduism MiniLM 0.388 0.415 0.459 0.686 0.416 (.2,.8) MiniLM + TAG 0.382 0.410 0.457 0.686 0.412 (.1,.8,.1) History MiniLM + TAG 0.740 0.735 0.764 0.862 0.730 (.2,.8,.0) Hsm MiniLM + TAG 0.666 0.707 0.737 0.870 0.690 (.2,.8,.0) Interpersonal MiniLM + TAG 0.663 0.617 0.653 0.739 0.604 (.2,.8,.0) Islam MiniLM 0.382 0.412 0.453 0.642 0.410 (.1,.9) MiniLM + TAG 0.395 0.427 0.464 0.642 0.421 (.1,.8,.1) Judaism MiniLM + TAG 0.363 0.387 0.432 0.649 0.388 (.2,.8,.0) Law MiniLM 0.663 0.647 0.678 0.803 0.639 (.2,.8) MiniLM + TAG 0.677 0.657 0.687 0.803 0.649 (.1,.8,.1) Lifehacks MiniLM 0.714 0.601 0.617 0.703 0.553 (.1,.9) MiniLM + TAG 0.714 0.621 0.631 0.703 0.568 (.1,.8,.1) Linguistics MiniLM + TAG 0.584 0.588 0.630 0.794 0.587 (.2,.8,.0) Literature MiniLM + TAG 0.871 0.878 0.889 0.934 0.876 (.3,.7,.0) Martialarts MiniLM 0.630 0.599 0.645 0.796 0.596 (.1,.9) MiniLM + TAG 0.640 0.628 0.660 0.796 0.612 (.1,.8,.1) Money MiniLM 0.545 0.535 0.563 0.706 0.515 (.2,.8) MiniLM + TAG 0.559 0.542 0.571 0.706 0.523 (.1,.8,.1) Movies MiniLM 0.713 0.722 0.753 0.865 0.724 (.1,.9) MiniLM + TAG 0.728 0.735 0.762 0.865 0.735 (.1,.8,.1) Music MiniLM 0.508 0.447 0.476 0.602 0.418 (.2,.8) MiniLM + TAG 0.522 0.460 0.486 0.602 0.427 (.1,.8,.1) Musicfans MiniLM + TAG 0.531 0.531 0.560 0.693 0.539 (.1,.9,.0) Opensource MiniLM 0.574 0.593 0.621 0.771 0.581 (.2,.8) MiniLM + TAG 0.577 0.598 0.622 0.771 0.581 (.1,.8,.1) Outdoors MiniLM + TAG 0.681 0.643 0.675 0.819 0.629 (.1,.9,.0) Parenting MiniLM + TAG 0.485 0.430 0.452 0.602 0.399 (.1,.9,.0) Pets MiniLM 0.509 0.531 0.565 0.685 0.523 (.1,.9) MiniLM + TAG 0.519 0.549 0.581 0.685 0.541 (.1,.8,.1) Philosophy MiniLM + TAG 0.568 0.514 0.546 0.707 0.491 (.2,.8,.0) Politics MiniLM + TAG 0.659 0.630 0.659 0.814 0.608 (.1,.9,.0) Rpg MiniLM 0.657 0.646 0.685 0.849 0.640 (.2,.8) MiniLM + TAG 0.677 0.660 0.695 0.849 0.651 (.1,.8,.1) Scifi MiniLM 0.532 0.563 0.596 0.745 0.559 (.2,.8) MiniLM + TAG 0.549 0.574 0.606 0.745 0.569 (.1,.8,.1) Skeptics MiniLM + TAG 0.862 0.869 0.887 0.969 0.867 (.2,.8,.0) Sound MiniLM 0.377 0.410 0.451 0.626 0.405 (.2,.8) MiniLM + TAG 0.380 0.423 0.454 0.626 0.413 (.1,.8,.1) Sports MiniLM 0.673 0.721 0.756 0.902 0.724 (.2,.8) MiniLM + TAG 0.692 0.743 0.775 0.902 0.740 (.1,.8,.1) Sustainability MiniLM 0.657 0.677 0.735 0.895 0.675 (.1,.9) MiniLM + TAG 694 0.716 0.763 0.895 0.706 (.1,.8,.1) Travel MiniLM + TAG 0.546 0.547 0.576 0.700 0.530 (.1,.9,.0) Vegetarianism MiniLM + TAG 0.623 0.626 0.678 0.869 0.641 (.3,.7,.0) Woodworking MiniLM + TAG 0.656 0.654 0.692 0.847 0.645 (.2,.8,.0) Workplace MiniLM + TAG 0.574 0.444 0.429 0.495 0.359 (.3,.7,.0) Writers MiniLM + TAG 0.561 0.490 0.516 0.644 0.466 (.2,.8,.0) Average MiniLM 0.519 0.506 0.536 0.677 0.492 - MiniLM + TAG 0.530 0.515 0.544 0.677 0.500 -

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