{"id":"https://openalex.org/W2096678023","doi":"https://doi.org/10.3115/v1/p14-2033","title":"Effective Document-Level Features for Chinese Patent Word Segmentation","display_name":"Effective Document-Level Features for Chinese Patent Word Segmentation","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2096678023","doi":"https://doi.org/10.3115/v1/p14-2033","mag":"2096678023"},"language":"en","primary_location":{"id":"doi:10.3115/v1/p14-2033","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/p14-2033","pdf_url":"https://aclanthology.org/P14-2033.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/P14-2033.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100391312","display_name":"Si Li","orcid":"https://orcid.org/0000-0001-7545-585X"},"institutions":[{"id":"https://openalex.org/I6902469","display_name":"Brandeis University","ror":"https://ror.org/05abbep66","country_code":"US","type":"education","lineage":["https://openalex.org/I6902469"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Si Li","raw_affiliation_strings":["Brandeis University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brandeis University","institution_ids":["https://openalex.org/I6902469"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036715761","display_name":"Nianwen Xue","orcid":"https://orcid.org/0000-0002-4364-3618"},"institutions":[{"id":"https://openalex.org/I6902469","display_name":"Brandeis University","ror":"https://ror.org/05abbep66","country_code":"US","type":"education","lineage":["https://openalex.org/I6902469"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nianwen Xue","raw_affiliation_strings":["Brandeis University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brandeis University","institution_ids":["https://openalex.org/I6902469"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I6902469"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"199","last_page":"205"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6744237542152405},{"id":"https://openalex.org/keywords/government","display_name":"Government (linguistics)","score":0.6611135601997375},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6549291610717773},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6154857873916626},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5704493522644043},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.559390664100647},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.539536714553833},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5010433197021484},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.49793243408203125},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.46465128660202026},{"id":"https://openalex.org/keywords/text-segmentation","display_name":"Text segmentation","score":0.45894068479537964},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.38617825508117676},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.2744845151901245},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.09186604619026184}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6744237542152405},{"id":"https://openalex.org/C2778137410","wikidata":"https://www.wikidata.org/wiki/Q2732820","display_name":"Government (linguistics)","level":2,"score":0.6611135601997375},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6549291610717773},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6154857873916626},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5704493522644043},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.559390664100647},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.539536714553833},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5010433197021484},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.49793243408203125},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.46465128660202026},{"id":"https://openalex.org/C98501671","wikidata":"https://www.wikidata.org/wiki/Q1948408","display_name":"Text segmentation","level":3,"score":0.45894068479537964},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.38617825508117676},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.2744845151901245},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.09186604619026184},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3115/v1/p14-2033","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/p14-2033","pdf_url":"https://aclanthology.org/P14-2033.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.654.5175","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.654.5175","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://aclweb.org/anthology/P/P14/P14-2033.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.3115/v1/p14-2033","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/p14-2033","pdf_url":"https://aclanthology.org/P14-2033.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W2096678023.pdf"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W57497961","https://openalex.org/W61584101","https://openalex.org/W1498441903","https://openalex.org/W1512811194","https://openalex.org/W1558333962","https://openalex.org/W1575907248","https://openalex.org/W2036516910","https://openalex.org/W2072278013","https://openalex.org/W2096204319","https://openalex.org/W2126504272","https://openalex.org/W2127626780","https://openalex.org/W2137766873","https://openalex.org/W2142146323","https://openalex.org/W2143026224","https://openalex.org/W2145905222","https://openalex.org/W2147880316","https://openalex.org/W2159406587","https://openalex.org/W2163377725","https://openalex.org/W2165345215","https://openalex.org/W2165664509","https://openalex.org/W2233156216","https://openalex.org/W2250623963","https://openalex.org/W2251797597","https://openalex.org/W2252264945","https://openalex.org/W2785522575"],"related_works":["https://openalex.org/W2159790760","https://openalex.org/W2978383222","https://openalex.org/W2172629291","https://openalex.org/W2380773642","https://openalex.org/W2384559435","https://openalex.org/W2337707338","https://openalex.org/W2393940967","https://openalex.org/W2058548953","https://openalex.org/W2785359773","https://openalex.org/W2385598138"],"abstract_inverted_index":{"A":[0],"patent":[1],"is":[2],"a":[3,19,54,66,72,99],"property":[4],"right":[5],"for":[6],"an":[7],"inven-tion":[8],"granted":[9],"by":[10],"the":[11,14,81,92],"government":[12],"to":[13,57],"in-ventor.":[15],"Patents":[16],"often":[17],"have":[18],"high":[20,42],"con-centration":[21],"of":[22,74,83],"scientific":[23,35],"and":[24,36,95],"technical":[25,37],"terms":[26,38],"that":[27,80],"are":[28],"rare":[29],"in":[30,45],"everyday":[31],"language.":[32],"How-ever,":[33],"some":[34],"usually":[39],"appear":[40],"with":[41],"frequency":[43],"only":[44],"one":[46],"specific":[47],"patent.":[48],"In":[49],"this":[50],"paper,":[51],"we":[52,64],"propose":[53],"pragmatic":[55],"approach":[56],"Chinese":[58],"word":[59],"segmentation":[60],"on":[61,71,91,98],"patents":[62],"where":[63],"train":[65],"sequence":[67],"labeling":[68],"model":[69,85],"based":[70],"group":[73],"novel":[75],"document-level":[76],"features.":[77],"Experiments":[78],"show":[79],"accuracy":[82],"our":[84],"reached":[86],"96.3":[87],"%":[88,97],"(F1":[89],"score)":[90],"de-velopment":[93],"set":[94],"95.0":[96],"held-out":[100],"test":[101],"set.":[102],"1":[103]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
