Sarcasm detection is considered one of the most challenging tasks in sentiment analysis and opinion mining applications in the social media. Sarcasm identification is therefore essential for a good public opinion decision. There are some studies on sarcasm detection that apply standard word2vec model and have shown great performance with word-level analysis. However, once a sequence of terms is being tackled, the performance drops. This is because averaging the embedding of each term in a sentence to get the general embedding would discard the important embedding of some terms. LSTM showed significant improvement in terms of document embedding. However, within the classification LSTM requires adding additional information in order to precisely classify the document into sarcasm or not. This study aims to propose two technique based on LSTM and Auto-Encoder for improving the sarcasm detection. A benchmark dataset has been used in the experiments along with several pre-processing operations that have been applied. These include stop word removal, tokenization and special character removal with LSTM which can be represented by configuring the document embedding and using Auto-Encoder the classifier that was trained on the proposed LSTM. Results showed that the proposed LSTM with Auto-Encoder outperformed the baseline by achieving 84% of f-measure for the dataset. The main reason behind the superiority is that the proposed auto encoder is processing the document embedding as input and attempt to output the same embedding vector. This will enable the architecture to learn the interesting embedding that have significant impact on sarcasm polarity.
Blockchain is an innovative technology that has gained interest in all sectors in the era of digital transformation where it manages transactions and saves them in a database. With the increasing financial transactions and the rapidly developed society with growing businesses many people looking for the dream of a better financially independent life, stray from large corporations and organizations to form startups and small businesses. Recently, the increasing demand for employees or institutes to prepare and manage contracts, papers, and the verifications process, in addition to human mistakes led to the emergence of a smart contract. The smart contract has been developed to save time and provide more confidence while dealing, as well as to cover the security aspects of digital management and to solve negotiation concerns. The smart contract was employed in creating a distributed ledger to eliminate the need for centralization. In this paper, a simple prototype has been implemented for the smart contract integrated with blockchain which is simulated in a local server with a set of nodes. Several security objectives, such as confidentiality, authorization, integrity, and non-repudiation, have been achieved in the proposed system. Besides, the paper discussed the importance of using the Blockchain technique, and how it contributed to the management of transactions in addition to how it was implemented in highly transparent real-estate scenarios. The smart contract was employed in creating a distributed ledger to eliminate the need for centralization. The elliptic-curve public key has been adopted as an alternative for the RSA in a signature generation/verification process and encryption protocol. For secure transactions, The Secure Socket Layer (SSL) also has been adopted as a secure layer in the web browser. The results have been investigated and evaluated from different aspects and the implementation was in a restricted environment. Experiments showed us the complexity of time and cost when using the (ECC) algorithm and using (RSA) algorithm depending on the size and length of the key. So if the size of the key in (ECC) equals (160) bits, and it corresponds to (1024) bits in (RSA), which is equivalent to 40% for (ECC) and 30% for (RSA). As a result, the (ECC) algorithm is complex, its key is smaller and the process of generating the key is faster, so it has achieved a high level of security.
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