The Role of a Natural Language Conversational Interface in Online Sales: A Case Study

This paper describes the evaluation of a natural language dialog-based navigation system (HappyAssistant) that helps users access e-commerce sites to find relevant information about products and services. The prototype system leverages technologies in natural language processing and human-computer interaction to create a faster and more intuitive way of interacting with websites, especially for less experienced users. The result of a comparative study shows that users prefer the natural language-enabled navigation two to one over the menu driven navigation. In addition, the study confirmed the efficiency of using natural language dialog in terms of the number of clicks and the amount of time required to obtain the relevant information. In the case study, as compared to the menu driven system, the average number of clicks used in the natural language system was reduced by 63.2% and the average time was reduced by 33.3%.     

A topic-based term frequency normalization framework to enhance probabilistic information retrieval

Many well-known probabilistic information retrieval models have shown promise for use in document ranking, especially BM25. Nevertheless, it is observed that the control parameters in BM25 usually need to be adjusted to achieve improved performance on different data sets; additionally, the assumption in BM25 on the bag-of-words model prevents its direct utilization of rich information that lies at the sentence or document level. Inspired by the above challenges with respect to BM25, we first propose a new normalization method on the term frequency in BM25 (called BM25_QL in this paper); in addition, the method is incorporated into CRTER₂, a recent BM25-based model, to construct CRTER₂^QL. Then, we incorporate topic modeling and word embedding into BM25 to relax the assumption of the bag-of-words model. In this direction, we propose a topic-based retrieval model, TopTF, for BM25, which is then further incorporated into the language model (LM) and the multiple aspect term frequency (MATF) model. Furthermore, an enhanced topic-based term frequency normalization framework, ETopTF, based on embedding is presented. Experimental studies demonstrate the great effectiveness and performance of these methods. Specifically, on all tested data sets and in terms of the mean average precision (MAP), our proposed models, BM25_QL and CRTER₂^QL, are comparable to BM25 and CRTER₂ with the best b parameter value; the TopTF models significantly outperform the baselines, and the ETopTF models could further improve the TopTF in terms of the MAP.     

Polymer electrolyte membranes from fluorinated polyisoprene-block-sulfonated polystyrene: Microdomain orientation by external field

In this study, block copolymer ionomers of the cesium salt (20 mol %) of fluorinated polyisoprene-block-sulfonated polystyrene were spin cast into membranes and annealed under an electric field of ∼40 V/μm at 130 °C for 24 h. The effect of this treatment was a 2.5 times increase in the ionic conductivity as measured by electrochemical impedance spectroscopy, under all humidity conditions measured. This can be attributed to the increased connectivity of the ionic domains of the block copolymers. This E-field alignment technique may thus find application in the fabrication of nanostructured polyelectrolytes with enhanced charge transport capacity.     

Mining of High-Utility Patterns in Big IoT-based Databases

When focusing on the general area of data mining, high-utility itemset mining (HUIM) can be defined as an offset of frequent itemset mining (FIM). It is known to emphasize more factors critically, which gives HUIM its intrinsic edge. Due to the flourishing development of the IoT technique, the uncertainty patterns mining is also attractive. Potential high-utility itemset mining (PHUIM) is introduced to reveal valuable patterns in an uncertainty database. Unfortunately, even though the previous methods are all very effective and powerful to mine, the potential high-utility itemsets quickly. These algorithms are not specifically designed for a database with an enormous number of records. In the previous methods, uncertainty transaction datasets would be load in the memory ultimately. Usually, several pre-defined operators would be applied to modify the original dataset to reduce the seeking time for scanning the data. However, it is impracticable to apply the same way in a big-data dataset. In this work, a dataset is assumed to be too big to be loaded directly into memory and be duplicated or modified; then, a MapReduce framework is proposed that can be used to handle these types of situations. One of our main objectives is to attempt to reduce the frequency of dataset scans while still maximizing the parallelization of all processes. Through in-depth experimental results, the proposed Hadoop algorithm is shown to perform strongly to mine all of the potential high-utility itemsets in a big-data dataset and shows excellent performance in a Hadoop computing cluster.

     

Passage extraction and result combination for genomics information retrieval

In this paper, we first propose algorithms for passage extraction to build indices for the purpose of generating more accurate passages as query answers. Second, we propose a basic result combination method and an improved result combination method to combine the retrieved results from different indices for the purpose of selecting and merging relevant passages as outputs. For passage extraction, three new algorithms are proposed, namely paragraphParsed, sentenceParsed and wordSentenceParsed. For result combination, a novel method is proposed, in which we use factor analysis to generate a better baseline result for combination by finding some hidden common factors that can be used to estimate the importance of keywords and keyword associations. Finally, we report the experimental results that confirm the effectiveness and superiority of the factor analysis based method for result combination. Our proposed approaches achieve excellent results on the TREC 2006 and 2007 Genomics data sets, which provide a promising avenue for constructing high performance information retrieval systems in biomedicine.     

Oxidative degradation of 4‐nitrophenol in UV‐illuminated titania suspension

An internally‐irradiated annular photoreactor has been used to investigate the oxidative degradation of aqueous 4‐nitrophenol with titania as the photocatalyst. Reaction runs were performed over a 3‐h period and in practically all cases, complete degradation was possible within about 2 h. The kinetics was determined as a function of nitrophenol concentration, oxygen partial pressure, catalyst loading, pH, temperature and light intensity. The reaction was characterised by a relatively low activation energy of 7.83 kJ mol^?1 although transport intrusions were negligible. Rate decreased almost exponentially with pH while a quadratic (maximum) behaviour with respect to both oxygen pressure and nitrophenol concentration is symptomatic of self‐inhibition possibly due to the formation of intermediates which competitively adsorb on similar sites to the reactants. Increased catalyst dosage also improved the reaction rate although the possible effects of light scattering and solution opacity caused a drop at loadings higher than about 1.20 g dm^?3. Rate, however, has a linear dependency on light intensity, suggesting that hole–electron recombination processes were negligible at the conditions investigated. © 2001 Society of Chemical Industry     

Dynamic study of polystyrene-block-poly(4-vinylpyridine) copolymer in bulk and confined in cylindrical nanopores

AAO template is highly recommended to nanostructure polymers and to study polymer properties under confinement. The dynamic properties of polystyrene-block-poly(4-vinylpyridine) (PS-b-P4VP) under confinement using broadband dielectric spectroscopy are investigated in this work and the results compared to those of the bulk. Anodized aluminum oxide (AAO) membranes, having pore diameters from tens to hundreds of nanometers in size, were used to confine PS-b-P4VP. Moreover, the influence of gold nanoparticles (AuNPs) in the copolymer matrix was also studied. The morphology and structure of the bulk copolymer and the copolymer confined in the AAO templates were characterized by transmission electron microscopy, scanning electron microscopy and Small Angle X-Ray Scattering. For PS-b-P4VP in bulk, dielectric relaxation techniques allowed studying selectively the P4VP segmental dynamics within the diblock. At high temperature this copolymer presents a dominant peak (MWS relaxation), most likely originated by the relatively high conductivity combined with the presence of interfaces emerging in the nanostructured samples. Moreover, a pronounced β-relaxation is observed for the copolymer compared with that of pure P4VP. This is likely due to a non-negligible contribution from the α-relaxation of the PS component. The γ-relaxation is markedly different in the copolymer, which is evidenced by a distinct temperature dependence of the resulting relaxation times. When the copolymer is embedded in alumina nanopores with small pore diameters (25 and 35 nm) there are significant changes, where the tendency is going to a faster dynamics when the pore diameter decreases more likely related to the relevance of surface effects. The presence of the AuNPs in the system enhances this effect. These results are in agreement with segregated structures found in the block copolymer by TEM and SAXS.     

(6<Emphasis Type="Italic">R</Emphasis>, 10<Emphasis Type="Italic">R</Emphasis>)-6,10,14-Trimethylpentadecan-2-one,a Dominant and Behaviorally Active Component in Male Orchid Bee Fragrances

6,10,14-Trimethylpentadecan-2-one (Hexahydrofarnesyl acetone; HHA) previously has been found to be a major component in tibial fragrances of male orchid bees, Euglossa spp. HHA is a chiral molecule with four possible stereoisomers, (6R, 10R)-, (6R, 10S)-, (6S, 10R)-, and (6S, 10S)-6,10,14-trimethylpentadecan-2-one. In the present study, we characterized HHA extracted from Euglossa as the pure enantiomer (6R, 10R)-6,10,14-trimethylpentadecan-2-one. During bioassays in Mexico and Panama, the synthetic RR-isomer attracted males of six species of orchid bees, including three that were known to contain HHA in their tibial fragrances. Possible sources of HHA for wild bees are flowers of euglossophilous orchids and aroids. With a molecular weight of 268, HHA is the largest natural molecule known to attract male orchid bees in pure form. Its attractiveness to males suggests that low-volatility compounds have a function in male signals, e.g., serve as a “base note” in complex odor bouquets.