{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:Q5QOFATSTZKMVSWB3N5VFOAAVD","short_pith_number":"pith:Q5QOFATS","schema_version":"1.0","canonical_sha256":"8760e282729e54cacac1db7b52b800a8d8757d048bfa42197e5199316eec77fb","source":{"kind":"arxiv","id":"1306.2864","version":1},"attestation_state":"computed","paper":{"title":"Finding Academic Experts on a MultiSensor Approach using Shannon's Entropy","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.AI","authors_text":"Andreas Wichert, Catarina Moreira","submitted_at":"2013-06-12T15:35:57Z","abstract_excerpt":"Expert finding is an information retrieval task concerned with the search for the most knowledgeable people, in some topic, with basis on documents describing peoples activities. The task involves taking a user query as input and returning a list of people sorted by their level of expertise regarding the user query. This paper introduces a novel approach for combining multiple estimators of expertise based on a multisensor data fusion framework together with the Dempster-Shafer theory of evidence and Shannon's entropy. More specifically, we defined three sensors which detect heterogeneous info"},"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":"1306.2864","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2013-06-12T15:35:57Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"722c9bea93eef68f085948da9dc1aa138d353ea62b88694afd9d216eda4e590d","abstract_canon_sha256":"a731dc1f7f71f099e94f13fad0c80c3322aeeb9df8d70f3d08ef171802076367"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:21:09.185151Z","signature_b64":"AbbY7nz3ybH83PVb3y6B0MatDyrngP8S826X0dsGk8mLVQIhXp8SqYbdoMAPfVn9HqI9KGWxeN0yuIJAdGoiCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8760e282729e54cacac1db7b52b800a8d8757d048bfa42197e5199316eec77fb","last_reissued_at":"2026-05-18T03:21:09.184555Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:21:09.184555Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Finding Academic Experts on a MultiSensor Approach using Shannon's Entropy","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.AI","authors_text":"Andreas Wichert, Catarina Moreira","submitted_at":"2013-06-12T15:35:57Z","abstract_excerpt":"Expert finding is an information retrieval task concerned with the search for the most knowledgeable people, in some topic, with basis on documents describing peoples activities. The task involves taking a user query as input and returning a list of people sorted by their level of expertise regarding the user query. This paper introduces a novel approach for combining multiple estimators of expertise based on a multisensor data fusion framework together with the Dempster-Shafer theory of evidence and Shannon's entropy. More specifically, we defined three sensors which detect heterogeneous info"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1306.2864","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":"1306.2864","created_at":"2026-05-18T03:21:09.184642+00:00"},{"alias_kind":"arxiv_version","alias_value":"1306.2864v1","created_at":"2026-05-18T03:21:09.184642+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1306.2864","created_at":"2026-05-18T03:21:09.184642+00:00"},{"alias_kind":"pith_short_12","alias_value":"Q5QOFATSTZKM","created_at":"2026-05-18T12:27:57.521954+00:00"},{"alias_kind":"pith_short_16","alias_value":"Q5QOFATSTZKMVSWB","created_at":"2026-05-18T12:27:57.521954+00:00"},{"alias_kind":"pith_short_8","alias_value":"Q5QOFATS","created_at":"2026-05-18T12:27:57.521954+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/Q5QOFATSTZKMVSWB3N5VFOAAVD","json":"https://pith.science/pith/Q5QOFATSTZKMVSWB3N5VFOAAVD.json","graph_json":"https://pith.science/api/pith-number/Q5QOFATSTZKMVSWB3N5VFOAAVD/graph.json","events_json":"https://pith.science/api/pith-number/Q5QOFATSTZKMVSWB3N5VFOAAVD/events.json","paper":"https://pith.science/paper/Q5QOFATS"},"agent_actions":{"view_html":"https://pith.science/pith/Q5QOFATSTZKMVSWB3N5VFOAAVD","download_json":"https://pith.science/pith/Q5QOFATSTZKMVSWB3N5VFOAAVD.json","view_paper":"https://pith.science/paper/Q5QOFATS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1306.2864&json=true","fetch_graph":"https://pith.science/api/pith-number/Q5QOFATSTZKMVSWB3N5VFOAAVD/graph.json","fetch_events":"https://pith.science/api/pith-number/Q5QOFATSTZKMVSWB3N5VFOAAVD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/Q5QOFATSTZKMVSWB3N5VFOAAVD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/Q5QOFATSTZKMVSWB3N5VFOAAVD/action/storage_attestation","attest_author":"https://pith.science/pith/Q5QOFATSTZKMVSWB3N5VFOAAVD/action/author_attestation","sign_citation":"https://pith.science/pith/Q5QOFATSTZKMVSWB3N5VFOAAVD/action/citation_signature","submit_replication":"https://pith.science/pith/Q5QOFATSTZKMVSWB3N5VFOAAVD/action/replication_record"}},"created_at":"2026-05-18T03:21:09.184642+00:00","updated_at":"2026-05-18T03:21:09.184642+00:00"}