{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:DY34NJINCBGEFXQAI6VVJ3GOMZ","short_pith_number":"pith:DY34NJIN","schema_version":"1.0","canonical_sha256":"1e37c6a50d104c42de0047ab54ecce66795533a49e8bf38fc68fc6b1ddc1d1b7","source":{"kind":"arxiv","id":"1907.00687","version":1},"attestation_state":"computed","paper":{"title":"A Capsule Network for Recommendation and Explaining What You Like and Dislike","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Chenliang Li, Cong Quan, Libing Wu, Li Peng, Yuming Deng, Yunwei Qi","submitted_at":"2019-07-01T12:12:00Z","abstract_excerpt":"User reviews contain rich semantics towards the preference of users to features of items. Recently, many deep learning based solutions have been proposed by exploiting reviews for recommendation. The attention mechanism is mainly adopted in these works to identify words or aspects that are important for rating prediction. However, it is still hard to understand whether a user likes or dislikes an aspect of an item according to what viewpoint the user holds and to what extent, without examining the review details. Here, we consider a pair of a viewpoint held by a user and an aspect of an item a"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1907.00687","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2019-07-01T12:12:00Z","cross_cats_sorted":[],"title_canon_sha256":"eb4e6c25b158b460c1eaa1ead7065e93bbeb9e8a1703e045eb9a08455e78d9a6","abstract_canon_sha256":"9a0d3fb09c68ab7b13edc7375ce8f8326f328f711adc60a22e2ca1cca47f6b85"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:41:50.766944Z","signature_b64":"Ohzpv8nkC9RNkEckZudN4dWO1DGL3JlxS0kLWSxMn8M7SIWgWEEm3F7FmIy2VaFobLinqymWhoef9QJH0h9eAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1e37c6a50d104c42de0047ab54ecce66795533a49e8bf38fc68fc6b1ddc1d1b7","last_reissued_at":"2026-05-17T23:41:50.766302Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:41:50.766302Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Capsule Network for Recommendation and Explaining What You Like and Dislike","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Chenliang Li, Cong Quan, Libing Wu, Li Peng, Yuming Deng, Yunwei Qi","submitted_at":"2019-07-01T12:12:00Z","abstract_excerpt":"User reviews contain rich semantics towards the preference of users to features of items. Recently, many deep learning based solutions have been proposed by exploiting reviews for recommendation. The attention mechanism is mainly adopted in these works to identify words or aspects that are important for rating prediction. However, it is still hard to understand whether a user likes or dislikes an aspect of an item according to what viewpoint the user holds and to what extent, without examining the review details. Here, we consider a pair of a viewpoint held by a user and an aspect of an item a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.00687","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1907.00687","created_at":"2026-05-17T23:41:50.766417+00:00"},{"alias_kind":"arxiv_version","alias_value":"1907.00687v1","created_at":"2026-05-17T23:41:50.766417+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.00687","created_at":"2026-05-17T23:41:50.766417+00:00"},{"alias_kind":"pith_short_12","alias_value":"DY34NJINCBGE","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_16","alias_value":"DY34NJINCBGEFXQA","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_8","alias_value":"DY34NJIN","created_at":"2026-05-18T12:33:15.570797+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/DY34NJINCBGEFXQAI6VVJ3GOMZ","json":"https://pith.science/pith/DY34NJINCBGEFXQAI6VVJ3GOMZ.json","graph_json":"https://pith.science/api/pith-number/DY34NJINCBGEFXQAI6VVJ3GOMZ/graph.json","events_json":"https://pith.science/api/pith-number/DY34NJINCBGEFXQAI6VVJ3GOMZ/events.json","paper":"https://pith.science/paper/DY34NJIN"},"agent_actions":{"view_html":"https://pith.science/pith/DY34NJINCBGEFXQAI6VVJ3GOMZ","download_json":"https://pith.science/pith/DY34NJINCBGEFXQAI6VVJ3GOMZ.json","view_paper":"https://pith.science/paper/DY34NJIN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1907.00687&json=true","fetch_graph":"https://pith.science/api/pith-number/DY34NJINCBGEFXQAI6VVJ3GOMZ/graph.json","fetch_events":"https://pith.science/api/pith-number/DY34NJINCBGEFXQAI6VVJ3GOMZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DY34NJINCBGEFXQAI6VVJ3GOMZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DY34NJINCBGEFXQAI6VVJ3GOMZ/action/storage_attestation","attest_author":"https://pith.science/pith/DY34NJINCBGEFXQAI6VVJ3GOMZ/action/author_attestation","sign_citation":"https://pith.science/pith/DY34NJINCBGEFXQAI6VVJ3GOMZ/action/citation_signature","submit_replication":"https://pith.science/pith/DY34NJINCBGEFXQAI6VVJ3GOMZ/action/replication_record"}},"created_at":"2026-05-17T23:41:50.766417+00:00","updated_at":"2026-05-17T23:41:50.766417+00:00"}