FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4384697538> ?p ?o ?g. }

• W4384697538 endingPage "46" @default.
• W4384697538 startingPage "1" @default.
• W4384697538 abstract "Recent years have seen an exponential growth (+98% in 2022 w.r.t. the previous year) of the number of research articles in the few-shot learning field, which aims at training machine learning models with extremely limited available data. The research interest toward few-shot learning systems for Named Entity Recognition (NER) is thus at the same time increasing. NER consists in identifying mentions of pre-defined entities from unstructured text, and serves as a fundamental step in many downstream tasks, such as the construction of Knowledge Graphs, or Question Answering. The need for a NER system able to be trained with few-annotated examples comes in all its urgency in domains where the annotation process requires time, knowledge and expertise (e.g., healthcare, finance, legal), and in low-resource languages. In this survey, starting from a clear definition and description of the few-shot NER (FS-NER) problem, we take stock of the current state-of-the-art and propose a taxonomy which divides algorithms in two macro-categories according to the underlying mechanisms: model-centric and data-centric. For each category, we line-up works as a story to show how the field is moving toward new research directions. Eventually, techniques, limitations, and key aspects are deeply analyzed to facilitate future studies." @default.
• W4384697538 created "2023-07-20" @default.
• W4384697538 creator A5022700280 @default.
• W4384697538 creator A5080190737 @default.
• W4384697538 creator A5081965427 @default.
• W4384697538 date "2023-10-09" @default.
• W4384697538 modified "2023-10-18" @default.
• W4384697538 title "Few-shot Named Entity Recognition: definition, taxonomy and research directions" @default.
• W4384697538 cites W1746680969 @default.
• W4384697538 cites W1982374456 @default.
• W4384697538 cites W1995875735 @default.
• W4384697538 cites W2056707879 @default.
• W4384697538 cites W2098830640 @default.
• W4384697538 cites W2111316763 @default.
• W4384697538 cites W2112511942 @default.
• W4384697538 cites W2144578941 @default.
• W4384697538 cites W2145339207 @default.
• W4384697538 cites W2156985047 @default.
• W4384697538 cites W2161044106 @default.
• W4384697538 cites W2168041406 @default.
• W4384697538 cites W2169099542 @default.
• W4384697538 cites W2252278997 @default.
• W4384697538 cites W2299976354 @default.
• W4384697538 cites W2528105143 @default.
• W4384697538 cites W2593560537 @default.
• W4384697538 cites W2620857485 @default.
• W4384697538 cites W2760505947 @default.
• W4384697538 cites W2785787385 @default.
• W4384697538 cites W2891383691 @default.
• W4384697538 cites W2891570996 @default.
• W4384697538 cites W2892248135 @default.
• W4384697538 cites W2898204262 @default.
• W4384697538 cites W2904415434 @default.
• W4384697538 cites W2911489562 @default.
• W4384697538 cites W2963051485 @default.
• W4384697538 cites W2963718112 @default.
• W4384697538 cites W2963845150 @default.
• W4384697538 cites W2963917673 @default.
• W4384697538 cites W2964006684 @default.
• W4384697538 cites W2964105864 @default.
• W4384697538 cites W2964114970 @default.
• W4384697538 cites W2966049804 @default.
• W4384697538 cites W2979826702 @default.
• W4384697538 cites W3006087551 @default.
• W4384697538 cites W3006227201 @default.
• W4384697538 cites W3011594683 @default.
• W4384697538 cites W3016415057 @default.
• W4384697538 cites W3034417881 @default.
• W4384697538 cites W3034718094 @default.
• W4384697538 cites W3034942609 @default.
• W4384697538 cites W3035067238 @default.
• W4384697538 cites W3045834900 @default.
• W4384697538 cites W3100806282 @default.
• W4384697538 cites W3131198033 @default.
• W4384697538 cites W3141797743 @default.
• W4384697538 cites W3173151551 @default.
• W4384697538 cites W3174282399 @default.
• W4384697538 cites W3176489198 @default.
• W4384697538 cites W3197893554 @default.
• W4384697538 cites W3212769596 @default.
• W4384697538 cites W4224903953 @default.
• W4384697538 cites W4281558957 @default.
• W4384697538 cites W4290742115 @default.
• W4384697538 cites W4290874847 @default.
• W4384697538 cites W4312727753 @default.
• W4384697538 cites W4319163914 @default.
• W4384697538 cites W99485931 @default.
• W4384697538 doi "https://doi.org/10.1145/3609483" @default.
• W4384697538 hasPublicationYear "2023" @default.
• W4384697538 type Work @default.
• W4384697538 citedByCount "0" @default.
• W4384697538 crossrefType "journal-article" @default.
• W4384697538 hasAuthorship W4384697538A5022700280 @default.
• W4384697538 hasAuthorship W4384697538A5080190737 @default.
• W4384697538 hasAuthorship W4384697538A5081965427 @default.
• W4384697538 hasBestOaLocation W43846975381 @default.
• W4384697538 hasConcept C154945302 @default.
• W4384697538 hasConcept C162324750 @default.
• W4384697538 hasConcept C187736073 @default.
• W4384697538 hasConcept C202444582 @default.
• W4384697538 hasConcept C204321447 @default.
• W4384697538 hasConcept C23123220 @default.
• W4384697538 hasConcept C2522767166 @default.
• W4384697538 hasConcept C2776321320 @default.
• W4384697538 hasConcept C2779135771 @default.
• W4384697538 hasConcept C2780451532 @default.
• W4384697538 hasConcept C33923547 @default.
• W4384697538 hasConcept C41008148 @default.
• W4384697538 hasConcept C58642233 @default.
• W4384697538 hasConcept C59822182 @default.
• W4384697538 hasConcept C86803240 @default.
• W4384697538 hasConcept C9652623 @default.
• W4384697538 hasConceptScore W4384697538C154945302 @default.
• W4384697538 hasConceptScore W4384697538C162324750 @default.
• W4384697538 hasConceptScore W4384697538C187736073 @default.
• W4384697538 hasConceptScore W4384697538C202444582 @default.
• W4384697538 hasConceptScore W4384697538C204321447 @default.
• W4384697538 hasConceptScore W4384697538C23123220 @default.

• next