Estimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with the large increase in the volume of textual data that is produced daily. Traditional approaches for calculating the degree of similarity between two texts, based on the words they share, do not perform well with short texts because two similar texts may be written in different terms by employing synonyms. As a result, short texts should be semantically compared. In this paper, a semantic similarity measurement method between texts is presented which combines knowledge-based and corpus-based semantic information to build a semantic network that represents the relationship between the compared texts and extracts the degree of similarity between them. Representing a text as a semantic network is the best knowledge representation that comes close to the human mind's understanding of the texts, where the semantic network reflects the sentence's semantic, syntactical, and structural knowledge. The network representation is a visual representation of knowledge objects, their qualities, and their relationships. WordNet lexical database has been used as a knowledge-based source while the GloVe pre-trained word embedding vectors have been used as a corpus-based source. The proposed method was tested using three different datasets, DSCS, SICK, and MOHLER datasets. A good result has been obtained in terms of RMSE and MAE.
Hedging is a linguistic avoidance of full commitment or precision. It is the use of a vague language. The main objectives of this study are to
... Show MoreCrime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin
... Show MoreThe continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre
... Show MoreThe biological effects of pulsed N2-laser on the old world screw-worm fly, Chrysomya bezziana Villeneuve in the pupal stage were investigated. Different laser parameters were involved in this work. The old pupae of 1, 2, 3, 4 and 5 days were exposed to laser radiation during 10, 30 and 60 second with repetition rate 10, 20 and 30 pulse/second. The percent of normal adults emergence (female and male) was investigated. The results showed that the adults emergence was highly decreased as the repetition rate and exposure time increased when the pupae irradiated for 1, 2 and 3 days old as compared with 4 and 5 days. The results also indicated that the pupal period was significantly increased of irradiated pupae for 1, 2, 3 and 4 days old, whi
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It highlights the importance of assessing the demand for money function in Iraq through the understanding of the relationship between him and affecting the variables by searching the stability of this function and the extent of their influence in the Iraqi dinar exchange rate in order to know the amount of their contribution to the monetary policies of the Iraqi economy fee, as well as through study behavior of the demand for money function in Iraq and analyze the determinants of the demand for money for the period 1991-2013 and the impact of these determinants in the demand for money in Iraq.
And that the problem that we face is how to estimate the total demand for money in
... Show MoreRecent advancement in production technologist of manufacturing processes have left an important effects upon cost structure. Moreover the problem for providing necessary and adequate information for managerial decision making.
Therefore the cost – volume – profit analysis under the new activity based costing has replace the old method for Analysing the relation between C.V.P with respect to profit planning and control.
In brief the C.V.P object is to discuss the effect of changes on profit resulting from changes in sales volume, cost of manufacturing and selling price.
This study consists of four chapters:
The first chapter dea
... Show Moreيتطلب تحقيق تمايز الوحدة الاقتصادية في ظل استعمال تقنيات الأعمال الحديثة وازدياد المنافسة وعالمية الأعمال ضرورة الاهتمام بمستوى نوعية المنتجات وما تتطلبه هذه النوعية من كلف والتي تسمى بكلف النوعية، إذ ان العديد من الشركات العالمية قد قامت بدراسة وتحليل هذه الكلف ووضع برامج خاصة بها بهدف تخفيضها إلى أدنى حدٍ ممكن وبما يكفل تحقيق العديد من المنافع والتوفيرات في هذه الكلف وبما يرشد عملية اتخاذ القرارات
... Show MoreThyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
... Show MoreThere is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into
... Show Moreמטרת המחקר הזה היא לבדוק את שלושה סיפורים קצרים מהקובץ הראשון של אהרון אפלפלד , שנחשב ההצהרה הרשמית על היותו סופר השואה הראשון בישראל , המשותף לשלושת הסיפורים הוא הנימה של הגיבורים היוצאים למסע פיזי ונפשי לגלות את אשר אירע להם , מגמתו של המחקר היא לבדוק את הצורה המיוחדת שבה אפיין אפלפלד את גיבוריו שמעידים על כך , כי השואה היא החוויה המרה והקשה בקרב היהודים והשלכותיה נשארה טמונה בקרבם גם אחרי המלחמה ואחרי שנים
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