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The present work proposes an unsupervised approach for recognising relations between named entities from a large corpora based on crime in Indian states and union territories. Initially, named entities have been identified from the extracted crime corpus and certain pair of entities have been chosen that facilitates the crime analysis. Then the entity pairs with their intermediate context words have...
Online discussions about software applications generate a large amount of requirements-related information. This information can potentially be usefully applied in requirements engineering; however currently, there are few systematic approaches for extracting such information. To address this gap, we propose Canary, an approach for extracting and querying requirements-related information in online...
Along with the popularity of the internet, contents inside web databases also increase quickly. These data, hidden behind the query interfaces, are called deep web. These contents normally are not collected by the search engines. Many deep web contents related applications, like contents collection, topic-focused crawling, and data integration, are based on understanding the schema of these query...
Operation services are reusable and shareable units of configuration code executed by configuration management tools (CMTs), achieving continuous deployment and continuous delivery. With the prevalence of DevOps (Development and Operations), thousands of operation services have been developed for various software systems, and they are publicly available through the online repositories of popular CMTs...
Modern databases contain an enormous amount of information stored in a structured format. This information is processed to acquire knowledge. However, the process of information extraction from a Database System is cumbersome for non-expert users as it requires an extensive knowledge of DBMS languages. Therefore, an inevitable need arises to bridge the gap between user requirements and the provision...
Datamining is the process of extracting interesting information of patterns from large databases. One of the most important datamining task and well-researched is the association rules mining. It aims to find the interesting correlation and relations among sets of items in the transaction databases. One of the main problems related to the discovery of these associations that a decision maker faces...
In the era of media convergence, tremendous changes have taken place both in the forms of media communication and representation. Management and utilization of massive, heterogeneous media content becomes increasingly important. The explicit and implicit information embodied in the media content, especially for the video content, has not been fully exploited yet. Great value can be developed with...
Recently, with the development of the online social network, sentiment classification (SC) which determines opinions of people is a significant task in natural language processing. In this research, we propose a model which combines deep learning and sub-tree mining to resolve sentiment classification problem. Stanford Parser is used to extract the relation from the beginning to the end of the sentences...
In paper text summarization represented as a sentence scoring and selection process. The process is modeled as a multi-objective optimization problem. The proposed model attempts to find balance between coverage and redundancy in a summary. For solving the optimization problem a human learning optimization algorithm is utilized.
The emerging popularity and raise in users' posts on social media gave birth to numerous research challenges. Out of all challenges users' centric context information based recommendation is one prime research area to recommend jobs, events and movies. Here in this research work we focus on movie context aware recommendation and for this purpose, we analyze users' posted movie tweets to understand...
In order to integrate search results returning from several deep web query interfaces, this paper proposes a framework of deep web query result integration system for a specific domain, which provides unified records from selected web sources dynamically. It submits query conditions on a global interface to local query interfaces, and transforms each query result web page to a DOM tree, then discovers...
With the technical advances, multimedia data is growing exponentially. It is progressively vital to mine the information from a video database consequently. Finding association between things in a large video assumes an extensive part in the video information mining. In light of the innovative work in the previous years, use of association mining is developing in various areas, for example, surveillance,...
Every day, number of pages gets added on web which makes tracking of their links cumbersome. Due to this, problem of overloaded data has come up. This issue led researchers to thoroughly go through different aspects of Web Usage Mining (WUM). Another issue of traditional system is of recommendations which are also a part of WUM and Web logs. This paper proposed a system of recommendations which uses...
Meetings are an important communication and coordination activity of teams: status is discussed, new decisions are made, alternatives are considered, details are explained, information is presented, and new ideas are generated. As such, meetings contain a large amount of rich project information that is often not formally documented. Capturing all of this informal meeting information has been a topic...
Exploiting facts that are published online using semi-structured or unstructured formats is a highly complex task, pieces of data are typically published in isolation and periodically updated in a bulk fashion without any coordination. In this paper, we propose a new software pipeline tackling this issue and semantically lifting online facts as Linked Data in a continuous manner. Our solution, LinkedPolitics,...
With the outburst in the growth of the social networking, it is alarming how the youth could become a victim of social trapping and psychological depressions. Nowadays internet messaging service plays a vital role in the social networking paradigm. Internet messaging which previously was meant for communication however turned out to have adverse effects on youth and country. Increased exposure and...
There is an increasing use of social interaction contexts in the cross-enterprise manufacturing problem solving. To transform these massive and unstructured data into decision-support information for cross-enterprise manufacturing demand-capability matching, we present automated solutions to two phases: 1) extracting relationships based on a semi-supervised learning approach to derive formalized heterogeneous...
Identifying similar items to the ones provided as input to a search system, is a challenging task. The main issues concern not only the management of large collections of data, but also the profiling of the users, who usually have different opinions, tastes and expertise. In this paper we propose a preliminary investigation about the improvements in the accuracy of a search system provided by network...
Complex networks of direct relevance to biomedicine have not yet been fully mapped largely due to the incompleteness, isolation, and heterogeneity of data. The Semantic Web, by providing a technical framework for the integration and sharing of heterogeneous databases in different domains, can potentially enable more effective complex network mapping and analysis. However, the feasibility of using...
The number of web databases are increasing progressively day-by-day and are web accessible through HTML — based form. The data units that are encoded in the search result web page are in a particular structure and unstructured format and are needed for human browsing for applications like, comparison shopping, to rate a web resource, deep web collection etc. So, for machine processing, it is needed...
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