ATP: A holistic attention integrated approach to enhance ABSA

Aspect based sentiment analysis (ABSA) deals with the identification of the sentiment polarity of a review sentence towards a given aspect. Deep Learning sequential models like RNN, LSTM, and GRU are current state-of-the-art methods for inferring the sentiment polarity. These methods work well to capture the contextual relationship between the words of a review sentence. However, these methods are insignificant in capturing long-term dependencies. Attention mechanism plays a significant role by focusing only on the most crucial part of the sentence. In the case of ABSA, aspect position plays a vital role. Words near to aspect contribute more while determining the sentiment towards the aspect. Therefore, we propose a method that captures the position based information using dependency parsing tree and helps attention mechanism. Using this type of position information over a simple word-distance-based position enhances the deep learning model's performance. We performed the experiments on SemEval'14 dataset to demonstrate the effect of dependency parsing relation-based attention for ABSA

Relevance Feedback Based Query Expansion Model Using Borda Count and Semantic Similarity Approach

Pseudo-Relevance Feedback (PRF) is a well-known method of query expansion for improving the performance of information retrieval systems. All the terms of PRF documents are not important for expanding the user query. Therefore selection of proper expansion term is very important for improving system performance. Individual query expansion terms selection methods have been widely investigated for improving its performance. Every individual expansion term selection method has its own weaknesses and strengths. To overcome the weaknesses and to utilize the strengths of the individual method, we used multiple terms selection methods together. In this paper, first the possibility of improving the overall performance using individual query expansion terms selection methods has been explored. Second, Borda count rank aggregation approach is used for combining multiple query expansion terms selection methods. Third, the semantic similarity approach is used to select semantically similar terms with the query after applying Borda count ranks combining approach. Our experimental results demonstrated that our proposed approaches achieved a significant improvement over individual terms selection method and related state-of-the-art methods

A Literature Survey on Automatic Query Expansion for Effective Retrieval Task

In This paper, we present a survey of important work done on automatic query expansion. Automatic query expansion is the process of automatically supplementing additional terms or phrases to the original query and is considered an extremely promising technique to improve the retrieval effectiveness. In this survey, we discussed a large number of recent approaches to automatic query expansion that include linguistic based, corpus-specific based, query-specific based and search log based approaches. Some of them use lexical resource such as WordNet and other use search log and web data for query expansion. The following questions are also addressed in this work. Why the query expansion is important for information retrieval? What are the main steps of automatic query expansion? What approaches of automatic query expansion are available and how do they compare? What are the critical issues and research directions of automatic query expansion

Regulatory Roles of Noncoding RNAs in the Progression of Gastrointestinal Cancers and Health Disparities

Annually, more than a million individuals are diagnosed with gastrointestinal (GI) cancers worldwide. With the advancements in radio- and chemotherapy and surgery, the survival rates for GI cancer patients have improved in recent years. However, the prognosis for advanced-stage GI cancers remains poor. Site-specific GI cancers share a few common risk factors; however, they are largely distinct in their etiologies and descriptive epidemiologic profiles. A large number of mutations or copy number changes associated with carcinogenesis are commonly found in noncoding DNA regions, which transcribe several noncoding RNAs (ncRNAs) that are implicated to regulate cancer initiation, metastasis, and drug resistance. In this review, we summarize the regulatory functions of ncRNAs in GI cancer development, progression, chemoresistance, and health disparities. We also highlight the potential roles of ncRNAs as therapeutic targets and biomarkers, mainly focusing on their ethnicity-/race-specific prognostic value, and discuss the prospects of genome-wide association studies (GWAS) to investigate the contribution of ncRNAs in GI tumorigenesis

Vascular neoplasia masquerading as cellulitis and persistent hemorrhagic pericardial effusion

Tufted angioma and kaposiform hemangioendothelioma are considered to represent two ends of the spectrum of benign vascular neoplasms that predominantly present during infancy or early childhood. We report a rare case of a 5-month-old infant with complicated vascular neoplasm involving the pericardial cavity and skin over cervical region, masquerading as infective pericarditis with cellulitis. The patient responded dramatically to therapy with oral prednisolone and sirolimus, with a significant reduction of size of skin lesions and complete resolution of pericardial effusion over 8 weeks. The report also highlights the importance of a multidisciplinary team in managing such complicated cases