The application of linguistic processing to automatic abstract generation

One approach to the problem of generating abstracts by computer is to extract from a source text those sentences which give a strong indication of the central subject matter and findings of the paper. Not surprisingly, concatenations of extracted sentences show a lack of cohesion, due partly to the frequent occurrence of anaphoric references. This paper describes the text processing which was necessary to identify these anaphors so that they may be utilised in the enhancement of the sentence selection criteria. It is assumed that sentences which contain non-anaphoric nounphrases and introduce key concepts into the text are worthy of inclusion in an abstract. The results suggest that the key concepts are indeed identified but the abstracts are too long. Further recommendations are made to continue this work in abstracting which makes use of text structure

The application of linguistic processing to automatic abstract generation

One approach to the problem of generating abstracts by computer is to extract from a source text those sentences which give a strong indication of the central subject matter and findings of the paper. Not surprisingly, concatenations of extracted sentences show a lack of cohesion, due partly to the frequent occurrence of anaphoric references. This paper describes the text processing which was necessary to identity these anaphors so that they may be utilised in the enhancement of the sentence selection criteria. It is assumed that sentences which contain non-anaphoric nounphrases and introduce key concepts into the text are worthy of inclusion in an abstract. The results suggest that the key concepts are indeed identified but the abstracts are too long. Further recommendations are made to continue this work in abstracting which makes use of text structure

Harnessing the potential of ligninolytic enzymes for lignocellulosic biomass pretreatment

Abundant lignocellulosic biomass from various industries provides a great potential feedstock for the production of value-added products such as biofuel, animal feed, and paper pulping. However, low yield of sugar obtained from lignocellulosic hydrolysate is usually due to the presence of lignin that acts as a protective barrier for cellulose and thus restricts the accessibility of the enzyme to work on the cellulosic component. This review focuses on the significance of biological pretreatment specifically using ligninolytic enzymes as an alternative method apart from the conventional physical and chemical pretreatment. Different modes of biological pretreatment are discussed in this paper which is based on (i) fungal pretreatment where fungi mycelia colonise and directly attack the substrate by releasing ligninolytic enzymes and (ii) enzymatic pretreatment using ligninolytic enzymes to counter the drawbacks of fungal pretreatment. This review also discusses the important factors of biological pretreatment using ligninolytic enzymes such as nature of the lignocellulosic biomass, pH, temperature, presence of mediator, oxygen, and surfactant during the biodelignification process

Management options for established chemotherapy-induced peripheral neuropathy

10.1007/s00520-014-2289-xSupportive Care in CancerSCCA