Preserving the Hypernym Tree of WordNet in Dense Embeddings

In this paper, we provide a novel way to generate low-dimension (dense) vector embeddings for the noun and verb synsets in WordNet, so that the hypernym-hyponym tree structure is preserved in the embeddings. We call this embedding the sense spectrum (and sense spectra for embeddings). In order to create suitable labels for the training of sense spectra, we designed a new similarity measurement for noun and verb synsets in WordNet. We call this similarity measurement the hypernym intersection similarity (HIS), since it compares the common and unique hypernyms between two synsets. Our experiments show that on the noun and verb pairs of the SimLex-999 dataset, HIS outperforms the three similarity measurements in WordNet. Moreover, to the best of our knowledge, the sense spectra is the first dense embedding system that can explicitly and completely measure the hypernym-hyponym relationship in WordNet

Applications of Chitosan in Pulmonary Drug Delivery

Pulmonary administration is an effective method for treating lung and other diseases. Drugs can be transported directly to the lung by the pulmonary drug delivery system (PDDS). PDDS has the advantages of maintained local drug concentration, reduced side effects, controllable drug release, promoted drug absorption, prolonged drug action time, and improved patient compliance. Polymers have been extensively utilized to prepare novel PDDS. Among these polymers, chitosan (CS) is a natural cationic polysaccharide which is rich in its source. It has many unique physicochemical properties, good biocompatibility, and satisfactory biodegradability. CS has been a popular biomaterial in pharmaceutics for decades and is widely used in drug delivery. CS contains many amino groups. The contained positive charges can interact strongly with the negatively charged mucosa membranes, thereby facilitating CS adsorption on the mucosal surface, avoiding clearance by the cilia, and improving the adhesion and penetration rate on the cell membrane. Moreover, studies have shown that CS could open cell tight junctions, which would promote drug transportation across the epithelial tissue. Thus, CS is an especially suitable material for PDDS. In this chapter, we will focus on the research progress and the applications of CS in PDDS. Many representative and advanced studies on CS-based PDDS are reviewed in detail

An Analysis on the Learning Rules of the Skip-Gram Model

To improve the generalization of the representations for natural language processing tasks, words are commonly represented using vectors, where distances among the vectors are related to the similarity of the words. While word2vec, the state-of-the-art implementation of the skip-gram model, is widely used and improves the performance of many natural language processing tasks, its mechanism is not yet well understood. In this work, we derive the learning rules for the skip-gram model and establish their close relationship to competitive learning. In addition, we provide the global optimal solution constraints for the skip-gram model and validate them by experimental results.Comment: Published on the 2019 International Joint Conference on Neural Network