The book covers several entity and relation extraction techniques starting from the traditional feature-based techniques to the recent techniques using deep neural models. Two important focus areas of the book are – i) joint extraction techniques where the tasks of entity and relation extraction are jointly solved, and ii) extraction of complex relations where relation types can be N-ary and cross-sentence. The first part of the book introduces the entity and relation extraction tasks and explains the motivation in detail. It covers all the background machine learning concepts necessary to understand the entity and relation extraction techniques explained later. The second part of the book provides a detailed survey of the traditional entity and relation extraction problems covering several techniques proposed in the last two decades. The third part of the book focuses on joint extraction techniques which attempt to address both the tasks of entity and relation extraction jointly. Several joint extraction techniques are surveyed and summarized in the book. It also covers two joint extraction techniques in detail which are based on the authors’ work. The fourth and the last part of the book focus on complex relation extraction, where the relation types may be N-ary (having more than two entity arguments) and cross-sentence (entity arguments may span multiple sentences). The book highlights several challenges and some recent techniques developed for the extraction of such complex relations including the authors’ technique. The book also covers a few domain-specific applications where the techniques for joint extraction as well as complex relation extraction are applied.
The book covers several entity and relation extraction techniques starting from the traditional feature-based techniques to the recent techniques using deep neural models. Two important focus areas of the book are – i) joint extraction techniques where the tasks of entity and relation extraction are jointly solved, and ii) extraction of complex relations where relation types can be N-ary and cross-sentence. The first part of the book introduces the entity and relation extraction tasks and explains the motivation in detail. It covers all the background machine learning concepts necessary to understand the entity and relation extraction techniques explained later. The second part of the book provides a detailed survey of the traditional entity and relation extraction problems covering several techniques proposed in the last two decades. The third part of the book focuses on joint extraction techniques which attempt to address both the tasks of entity and relation extraction jointly. Several joint extraction techniques are surveyed and summarized in the book. It also covers two joint extraction techniques in detail which are based on the authors’ work. The fourth and the last part of the book focus on complex relation extraction, where the relation types may be N-ary (having more than two entity arguments) and cross-sentence (entity arguments may span multiple sentences). The book highlights several challenges and some recent techniques developed for the extraction of such complex relations including the authors’ technique. The book also covers a few domain-specific applications where the techniques for joint extraction as well as complex relation extraction are applied.
The year 2007 was game-changing for Indian cricket. In March that year, Indian cricket was rocked by the early exit at the 50-over World Cup in the Caribbean. However, in the months ahead, the team picked up the pieces and charted a path to recovery. In the backdrop was the ICC World T20 2007 - the first ever world championship in the format. India opted to back the youngsters, led by Mahendra Singh Dhoni. There were no expectations or the pressure of history. In South Africa, MS Dhoni and his men dazzled the public and clinched victory in a dramatic final against arch-rivals Pakistan. A lot happened on and off the field in the months between India's nadir and zenith that year. This book explores those events and recounts how Indian cricket changed in those months. The ripple effects of that victory are felt even today as India's cricket loving public embraced T20 cricket and created a big market for the format.
Fab Five is the story of the power-packed batting lineup of the Indian team comprising of Sourav Ganguly, Virender Sehwag, Sachin Tendulkar, VVS Laxman and Rahul Dravid; each of them legends in their own rights. The book goes back to Mahabharat and draws a parallel from the Pandavas who were legendary warriors. Based on their distinctive traits, each member of the Fab Five is equated to one of the Pandavas – Ganguly as Yudhishthir, Sehwag as Bheem, Tendulkar as Arjun, Laxman as Nakul and Dravid as Sahadev. Together, they scripted some of the most famous victories in the history of Indian cricket. While it was a collective team effort that led to the success and the contribution of other players were equally crucial, but it would not have been possible without this strong batting line-up. With the emergence of Fab Five, the days when India’s batting had a huge dependency on Tendulkar’s shoulders was a thing of the past. Each member of the Fab Five could win the match single-handedly on their day. Ganguly’s lofted sixes, Sehwag’s aggression, Tendulkar’s impeccable straight drives, Laxman’s artistry and Dravid’s assuring defense were a treat to the eyes of the cricket fans. It is a humble tribute to these five legends and a celebration of their contribution to Indian cricket.
The book is an act of retrieval, bringing back our forgotten heroes to life! A long overdue homage to the magnificent sportspeople, who thrived and reached the pinnacle by sheer individual genius, personal effort and immense sacrifice.
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