Results 81 to 90 of about 89,062 (279)
Word Mover’s Embedding: From Word2Vec to Document Embedding [PDF]
While the celebrated Word2Vec technique yields semantically rich representations for individual words, there has been relatively less success in extending to generate unsupervised sentences or documents embeddings. Recent work has demonstrated that a distance measure between documents called \emph{Word Mover's Distance} (WMD) that aligns semantically ...
Wu, Lingfei +7 more
openaire +2 more sources
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz +3 more
wiley +1 more source
Event-Driven Semantic Service Discovery Based on Word Embeddings
Service discovery is vital to event handling in Internet of Things applications which are based on the event-driven service-oriented architecture. However, in service discovery, the problem of service matching that establishes relationships between ...
Fagui Liu +3 more
doaj +1 more source
Investigating Word Meta-Embeddings by Disentangling Common and Individual Information
In the field of natural language processing, combining multiple pre-trained word embeddings has become a viable approach to improve word representations. However, there is still a lack of understanding of why such improvements can be achieved.
Wenfan Chen +3 more
doaj +1 more source
Mimicking Word Embeddings using Subword RNNs
Word embeddings improve generalization over lexical features by placing each word in a lower-dimensional space, using distributional information obtained from unlabeled data.
Eisenstein, Jacob +2 more
core +1 more source
Word Embeddings in Sentiment Analysis [PDF]
In the late years sentiment analysis and its applications have reached growing popularity. Concerning this field of research, in the very late years machine learning and word representation learning derived from distributional semantics field (i.e. word embeddings) have proven to be very successful in performing sentiment analysis tasks.
Petrolito R, Dell'Orletta F
openaire +1 more source
An All‐Optical Driven Bio‐Photovoltaic Interface for Active Control of Live Cells
Bio‐photovoltaic Interface (BIO‐PV‐I) for live cell manipulation is presented. BIO‐PV‐I can be activated non‐invasively and remotely to control the spatial motility, adhesion, and morphology of cells adhering to it. BIO‐PV‐I uses a patterned light‐induced electric potential in iron‐doped lithium niobate crystals whose light‐driven and reversible nature,
Lisa Miccio +8 more
wiley +1 more source
Predicting High-Level Human Judgment Across Diverse Behavioral Domains
Recent advances in machine learning, combined with the increased availability of large natural language datasets, have made it possible to uncover semantic representations that characterize what people know about and associate with a wide range of ...
Russell Richie +2 more
doaj +1 more source
Predicting Role Relevance with Minimal Domain Expertise in a Financial Domain
Word embeddings have made enormous inroads in recent years in a wide variety of text mining applications. In this paper, we explore a word embedding-based architecture for predicting the relevance of a role between two financial entities within the ...
Kejriwal, Mayank
core +1 more source
A FeN4─O/Clu@NC‐0.1Ac catalyst containing atomically‐dispersed FeN4─O sites (medium‐spin Fe2+) and Fe clusters delivered a half‐wave potential of 0.89 V for ORR and an overpotential of 330 mV at 10 mA cm−2 for OER in 0.1 m KOH. When the catalyst was used in a rechargeable Zn–air battery, a power density of 284.5 mW cm−2 was achieved with excellent ...
Yongfang Zhou +8 more
wiley +1 more source

