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Introduction to Algorithms PDF, ePub eBook

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Introduction to Algorithms

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Introduction to Algorithms PDF, ePub eBook This title covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept element This title covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.

30 review for Introduction to Algorithms

  1. 5 out of 5

    Shawn Morel

    What a terrible book. Though it's the cornerstone of many CS undergrad algorithm courses, this book fails in every way. In almost every way, Dasgupta and Papadimitriou's "Algorithms" is a much better choice: http://www.goodreads.com/book/show/13... It tries to be a reference book presenting a good summary of algorithms but any of the interesting bits are left as "exercises to the student." Many of these exercises are do-able but far from trivial mental connections. A few require some mental Ah Ha What a terrible book. Though it's the cornerstone of many CS undergrad algorithm courses, this book fails in every way. In almost every way, Dasgupta and Papadimitriou's "Algorithms" is a much better choice: http://www.goodreads.com/book/show/13... It tries to be a reference book presenting a good summary of algorithms but any of the interesting bits are left as "exercises to the student." Many of these exercises are do-able but far from trivial mental connections. A few require some mental Ah Ha moments. It fails at being a reference book It tries to be a text book (didactic) but it is too verbose and goes into too much depth on every topic along the way to be a useful guide. A possibly more useful organization would have been to have 2 virtual books, the first a much shorter textbook, the second an algorithm reference. It fails at being a text book It tries to be a workbook by presenting many exercises to the reader. The problem is that it provides inadequate scaffolding. It just goes ahead and gives you the answers to what could have been medium difficulty questions (since it's trying to be a mostly complete reference). This gives you no chance to flex your mental muscle on tractable problems. All of the harder problems are left as exercises without much help of how to approach them.

  2. 4 out of 5

    Khaled Alhourani

    An essential book for every programmer, you can't read this kind of book on bus, you need to fully constraint while reading it. The exercises after each chapter are very important to fully understand the chapter you just read, and to activate your brain's neurons. The book in itself is an outstanding one, very organized, focused and small chapters makes it easier to understand the algorithms inside it. It contains the essential and most popular algorithms, so you can't live wthout it if you are r An essential book for every programmer, you can't read this kind of book on bus, you need to fully constraint while reading it. The exercises after each chapter are very important to fully understand the chapter you just read, and to activate your brain's neurons. The book in itself is an outstanding one, very organized, focused and small chapters makes it easier to understand the algorithms inside it. It contains the essential and most popular algorithms, so you can't live wthout it if you are real programmer. You can skip chapters/read about an algorithm you want to understand more, as if there is a previous idea/algorithm the authors directly mention that with chapter's number so you can go directly to it for more information. I've read the 2nd edition, and now reading this one, the 3rd edition.

  3. 5 out of 5

    Saharvetes

    Rather pointless to review this, as in most places this is the algorithms textbook. It's a good book that covers all the major algorithms in sufficient detail with every step clearly spelled out for the students' benefit. Unfortunately, this neatness of presentation is also its most major drawback: (1) it spends more time describing algorithms than giving the reader an idea of how to design them, and (2) it can easily give the impression that algorithms is about spending a lot of time proving obv Rather pointless to review this, as in most places this is the algorithms textbook. It's a good book that covers all the major algorithms in sufficient detail with every step clearly spelled out for the students' benefit. Unfortunately, this neatness of presentation is also its most major drawback: (1) it spends more time describing algorithms than giving the reader an idea of how to design them, and (2) it can easily give the impression that algorithms is about spending a lot of time proving obvious correctness results, which is not how people think of algorithms in real life (whether in academia, or in "real world" applications). For this reason, I'd recommend not using this fat book, and instead using either Kleinberg and Tardos's Algorithm Design, or Dasgupta–Papadimitriou–Vazirani's Algorithms, or Skeina's The Algorithm Design Manual, which are all better at showing you how to think about algorithms the right way.

  4. 4 out of 5

    Alex

    While searching for a Bible of algorithms, I of course quickly gravitated towards Knuth's Art of Computer Programming series. It's thousands of pages long — a magnum opus still in progress; how could it not be the most desirable source? My research quickly yielded mixed opinions from the community. Some loved Knuth's books, while others found their language impenetrable, their code irrelevant, or their assertions wrong or out of date. All, on the other hand, universally praised Introduction to Al While searching for a Bible of algorithms, I of course quickly gravitated towards Knuth's Art of Computer Programming series. It's thousands of pages long — a magnum opus still in progress; how could it not be the most desirable source? My research quickly yielded mixed opinions from the community. Some loved Knuth's books, while others found their language impenetrable, their code irrelevant, or their assertions wrong or out of date. All, on the other hand, universally praised Introduction to Algorithms. While my exposure to Knuth's work is still minimal, I can certainly echo the praise for Intro. Intro's language is academic, but understandable. If one were to put Knuth's work on the "unreadable" extreme and O'Reilly's popular Head First series on the opposite extreme, Intro would fall somewhere in the middle, leaning towards Knuth. Intro very smartly uses pseudocode that doesn't attempt to resemble any popular programming language (with its own idiosyncratic syntax and responsibilities). Oftentimes I skip straight to the pseudocode examples, as I find them immensely readable and translatable into practical, functioning code of any language. This book is a must-have on the shelf of any computer scientist, and any practical programmer who wants to write more efficient code. Pick it up!

  5. 5 out of 5

    Nick Black

    An essential, well-written reference, and one it's quite possible to read through several times, picking up new info each time. That having been said....this book never, I felt, adequately communicated THE LOVE. The pseudocode employed throughout is absolutely wretched, at times (especially in later chapters) binding up and abstracting away subsidiary computational processes not with actual predefined functions but english descriptions of modifications thereof -- decide whether you're writing co An essential, well-written reference, and one it's quite possible to read through several times, picking up new info each time. That having been said....this book never, I felt, adequately communicated THE LOVE. The pseudocode employed throughout is absolutely wretched, at times (especially in later chapters) binding up and abstracting away subsidiary computational processes not with actual predefined functions but english descriptions of modifications thereof -- decide whether you're writing code samples for humans or humans-simulating-automata, please, and stick to one. This habit wouldn't be so obnoxious, save that several (although, admittedly, rare) "inline modifications of declaration" seem to require modifications of definition which would subsequently invalidate previous running-time or -space guarantees. As the STL if nothing else has taught us, usable spellbooks must include running-time analysis as part of their designs/contracts/documentations. I know the authors have released an updated edition; I do not yet own it, and could contrast with assurance only the two editions' coverage of string-matching algorithms. That minor nit having been aired, CLR1 belongs in undergraduate curricula and on pros' bookshelves. Its illustrations, in particular, are highly effective and bring several fundamental algorithms to life better than I've seen elsewhere; its treatment of the Master Method is the best I've seen with an undergraduate audience. I'd like some algorithms from modern machine learning theory (SVM's, etc) and also multi-string / fuzzy-string matching, but those are admittedly advanced topics. It's no Knuth, but it ain't bad.

  6. 5 out of 5

    Josh Davis

    I've been reading CLRS on and off for years. I read bits at a time and have been picking and choosing chapters to read and reread. I must say that without a doubt this is the best textbook I have ever read. I could not recommend it anymore for anyone that wishes to learn about data structures and algorithms well. The authors never skimp on the math and that's my favorite part of this book. Almost every idea that is presented is proven with a thorough proof. All of the pseudocode is completely go I've been reading CLRS on and off for years. I read bits at a time and have been picking and choosing chapters to read and reread. I must say that without a doubt this is the best textbook I have ever read. I could not recommend it anymore for anyone that wishes to learn about data structures and algorithms well. The authors never skimp on the math and that's my favorite part of this book. Almost every idea that is presented is proven with a thorough proof. All of the pseudocode is completely golden and thoroughly tested. Read this, seriously.

  7. 4 out of 5

    Arif

    Well, technically I didn't finish reading all the chapters in the book, but at least I've read most of it. The topics in the book is well explained with concise example. But sometimes, I need to find out the explanation by myself, things that I found interesting but sometimes frustrating. If I run into this situation, sometimes I need to find another reference to help me understand the problem. But still, this is a good book.

  8. 5 out of 5

    Koen Crolla

    Some people just really enjoy typing, I guess. Not so much communicating, though: I was already pretty familiar with almost all of the algorithms and data structures discussed (the bit on computational geometry was the only thing that was completely new), but I can honestly say that if Introduction to Algorithms had been my first textbook, I wouldn't be. (Also, I wish editors would stop writers when they try to use 1-indexed arrays in their books. Or, for that matter, pseudocode in general. Machi Some people just really enjoy typing, I guess. Not so much communicating, though: I was already pretty familiar with almost all of the algorithms and data structures discussed (the bit on computational geometry was the only thing that was completely new), but I can honestly say that if Introduction to Algorithms had been my first textbook, I wouldn't be. (Also, I wish editors would stop writers when they try to use 1-indexed arrays in their books. Or, for that matter, pseudocode in general. Machine-interpretable, human-readable high-level languages aren't a new concept.)

  9. 4 out of 5

    Blog on Books

    Algorithms, which perform some sequence of mathematical operations, form the core of computer programming. Intended as a text for computer programming courses, especially undergraduate courses in data structures and graduate courses in algorithms, an “Introduction to Algorithms” provides a comprehensive overview, that will be appreciated technical professionals, as well. The major topics presented are sorting, data structures, graph algorithms and a variety of selected topics. Computer programmer Algorithms, which perform some sequence of mathematical operations, form the core of computer programming. Intended as a text for computer programming courses, especially undergraduate courses in data structures and graduate courses in algorithms, an “Introduction to Algorithms” provides a comprehensive overview, that will be appreciated technical professionals, as well. The major topics presented are sorting, data structures, graph algorithms and a variety of selected topics. Computer programmers can draw desired algorithms directly from the text or use the clear explanations of the underlying mathematics to develop custom algorithms. The algorithms are presented in pseudocode that can be adapted to programming languages, such as C++ and Java. The focus is on design rather than implementation. While a solid background in advanced mathematics and probability theory is needed to fully appreciate the material, non-programmers and IT professionals (such as this reviewer) will appreciate the numerous tips provided for improving the efficiency and thus reducing the cost of developing applications. Any Computer Science student would find this text an essential resource, even if not specifically required for course work. However, the advanced mathematical principles needed to grasp the material are presented as exercises, intended to be worked through in class, so no solutions are provided, which may frustrate self-studiers and limit its utility as a reference. Although surprisingly well written, a book of this size and complexity is bound to have some errors. See http://mitpress.mit.edu/algorithms for the error list and supplemental information about the book (including solutions to some, but not all exercises, and an explanation of the corny professor jokes sprinkled throughout the text).

  10. 4 out of 5

    Sumit Gouthaman

    I think this book is incorrectly positioned as an "Introduction" to algorithms. If you are interested in learning algorithms, this should probably not be the first book you read. I would instead recommend Robert Sedgewick's book or course on Coursera. The problem with this comes down to the fact that is focuses too much on the mathematical details, while ignoring other interesting aspects. Many crucial aspects of classic algorithms are relegated to the exercises section instead of being covered fr I think this book is incorrectly positioned as an "Introduction" to algorithms. If you are interested in learning algorithms, this should probably not be the first book you read. I would instead recommend Robert Sedgewick's book or course on Coursera. The problem with this comes down to the fact that is focuses too much on the mathematical details, while ignoring other interesting aspects. Many crucial aspects of classic algorithms are relegated to the exercises section instead of being covered front and center. Even when covering important algorithms, the book glosses over important details. When it comes to implementing algorithms, I find the pseudo-code in this book much more complicated than it needs to be. Some examples that come to mind: 1. The quick sort discussion does not important / simpler approaches like 3 way quick sort. 2. The Red-Black trees implementation and explanation is much more complicated than the simpler approach described in Sedgewick's material. Overall, this book does have its merits. Once you've learned basic algorithms from another source, you can come back to this book to understand the underlying mathematical proofs. But I would not recommend this to be your "introduction" to algorithms.

  11. 4 out of 5

    Erik

    Final exam: completed. This damn textbook: ignored from here on out. Whenever I look at it now, all I can think of is Alex in Clockwork Orange: "Eggiwegs! I want to SMASH THEM!" This book did not help me in my class, not one tiny bit. Like so many other math-oriented textbooks, there is literally not one damn thing in the book that is not teachable but the teaching moments are all lost in math gymnastics, over-explaining, under-explaining, etc. Please, just once, let someone with the teaching tal Final exam: completed. This damn textbook: ignored from here on out. Whenever I look at it now, all I can think of is Alex in Clockwork Orange: "Eggiwegs! I want to SMASH THEM!" This book did not help me in my class, not one tiny bit. Like so many other math-oriented textbooks, there is literally not one damn thing in the book that is not teachable but the teaching moments are all lost in math gymnastics, over-explaining, under-explaining, etc. Please, just once, let someone with the teaching talent of Sal Khan (of Khan Academy) write a textbook about math. Just once. Why is that so hard? Just one textbook that is focused on teaching and not befuddling, obfuscating, or jerking students' chains; a book that is not 500 pages too long; a book that teaches fundamentals before moving on to fundamentals +1 and then fundamentals +2 (not jumping to fundamentals +1432)...I'm not holding my breath, no way. This will never happen because academic math people are writing the books. Know who would be a perfect algorithms textbook author? Someone that has to struggle through learning the subject matter just like a student. I'd buy that author's book. This one, though...let's just say I'm glad I got an international edition and not a full-price US/Canada edition. If I burn it, I'm only out $20.

  12. 5 out of 5

    Wouter

    It has ben 14 years since I touched a math-oriented theoretical work like this, and that hurt a lot while slogging through this textbook. After graduating a lot of the software engineering skills you pick up are geared towards practicality. I literally forgot some mathematical terms I had to look up again. Sadly, trying to understand it's lemma's with the help of the appendices is not doable as they are even heavier than the things they try to explain. Besides that problematic point, it's an exc It has ben 14 years since I touched a math-oriented theoretical work like this, and that hurt a lot while slogging through this textbook. After graduating a lot of the software engineering skills you pick up are geared towards practicality. I literally forgot some mathematical terms I had to look up again. Sadly, trying to understand it's lemma's with the help of the appendices is not doable as they are even heavier than the things they try to explain. Besides that problematic point, it's an excellent guide (but not an introduction!) into algorithms & data structures including classic problems as sorting and searching with lists, trees, graphs and the like. Some extra background is provided along with alternatives that amused me after implementing the default solution. If you're not studying CS or you have but it was a long time ago, there might be better things to read. But it's still worth it.

  13. 5 out of 5

    Sheikh

    This is an excellent book for software engineers and students of computer science and engineering who want to have a good understanding of algorithms.

  14. 4 out of 5

    Brad

    The textbook on algorithms. It does not do a very good job of teaching how to design algorithms, but it is an authoritative catalog of algorithms for a wide variety of situations.

  15. 4 out of 5

    Dmitry Kuzmenko

    The book gives a solid foundation of common non-trivial algorithms and data structures. It all comes with nice pseudocode, detailed walk-throughs and complexity analysis (along with worst case, average case and amortized complexity). Personally I'd prefer to see the material in much more compact form, covering more of topics and more advanced or tricky algorithms and data structures. However, when something isn't clear, the detailed walk-throughs really help. Also, the exercises provided are inva The book gives a solid foundation of common non-trivial algorithms and data structures. It all comes with nice pseudocode, detailed walk-throughs and complexity analysis (along with worst case, average case and amortized complexity). Personally I'd prefer to see the material in much more compact form, covering more of topics and more advanced or tricky algorithms and data structures. However, when something isn't clear, the detailed walk-throughs really help. Also, the exercises provided are invaluable. I'd say is a must-read for every software engineer and computer scientist. If you aren't already familiar with the content from other sources, it's really worth investing a couple of years in it: read the book, try everything out with your favorite programming language and do exercises. Comparing to Knuth's "The Art of Computer Programming", it is a ten times easier read.

  16. 4 out of 5

    Mohammad Samiul Islam

    This books is amazing. It's a bit hard for beginners, but then again, it's one of those books which you always have to come back to. Each time you come back, you learn something new. The exercises themselves have tons of stuff hidden in them. You need to be patient and learn slowly. Don't try to gobble everything up. If you let go of your fear, and actually make an effort to learn something from it, you can learn loads. I learned Network Flow algorithm by reading this book. It took me few days, b This books is amazing. It's a bit hard for beginners, but then again, it's one of those books which you always have to come back to. Each time you come back, you learn something new. The exercises themselves have tons of stuff hidden in them. You need to be patient and learn slowly. Don't try to gobble everything up. If you let go of your fear, and actually make an effort to learn something from it, you can learn loads. I learned Network Flow algorithm by reading this book. It took me few days, but I did manage to learn the algorithm myself by reading just this book.

  17. 4 out of 5

    Michael

    This is one of the worst college books I have ever used. The examples in the book are severely lacking the needed information to answer the questions in which you are forced to use outside resources aka other Data Structure books to find the info to solve their problems. It is amazing that this is an MIT book because it DOES NOT MEET THEIR STANDARD. The book is unorganized and bounces around like the authors have ADHD. The text is covering an extremely abstract computer algorithm theories and fa This is one of the worst college books I have ever used. The examples in the book are severely lacking the needed information to answer the questions in which you are forced to use outside resources aka other Data Structure books to find the info to solve their problems. It is amazing that this is an MIT book because it DOES NOT MEET THEIR STANDARD. The book is unorganized and bounces around like the authors have ADHD. The text is covering an extremely abstract computer algorithm theories and fails to provided the needed information to support understanding of the material.

  18. 5 out of 5

    Harshil Lodhi

    A book that one should definitely read once in the computer science career. It gives a mathematical and in depth look at how to understand algorithms and data structures, their time and space complexities and its proofs. It could be a little hard, complex and lengthy for those who don't like in depth mathematics or those who just want to understand the DS and Algo at application level. It is a classic and available for free so one should definitely read it.

  19. 5 out of 5

    Kaung Htet Zaw

    One of the best algorithm textbooks out there. Always my go-to book for algorithm reference.

  20. 5 out of 5

    Andrew Obrigewitsch

    This is the definitive book on algorithms.

  21. 4 out of 5

    Antonis Maronikolakis

    This book kick-started my love for algorithm design. Not only is it an in-depth introduction to algorithms, providing a complete guide on the basics, it is also expertly written. The concepts are laid out in an intuitive and easy to follow manner, while also going into more detail for those who want to learn more. I highly suggest this book. Offers a very thorough and clean introduction to the basics of algorithm design, while also going very in depth in later chapters. It also includes an Append This book kick-started my love for algorithm design. Not only is it an in-depth introduction to algorithms, providing a complete guide on the basics, it is also expertly written. The concepts are laid out in an intuitive and easy to follow manner, while also going into more detail for those who want to learn more. I highly suggest this book. Offers a very thorough and clean introduction to the basics of algorithm design, while also going very in depth in later chapters. It also includes an Appendix for Math stuff, which has come in handy many times I need a refresh in memory. The book has some math heavy chapters, but mostly the math you’ll find are easily digestible. The last chapter presents a wide range of topics, from Linear Programming to String Matching. A particularly good read is the Approximation Algorithms, which presents some very interesting concepts and problems. There is also a chapter for Graph Algorithms where the authors go in depth on some of the most well known such algorithms. Very interesting read that helps get a better feel of how the algorithms work. There is also a chapter for Advanced Data Structures, which offers a very detailed view of some of the lesser known structures, like Fibonacci Heaps. Also a very interesting read, although it does become a bit hard to follow at times. One big plus for this book is the exercises at the end of every chapter. Even though they do not have any solutions (although you can easily find them online), they are very interesting and also very helpful in understanding the concepts presented in the chapter. This is a book every Computer Scientist should have in his collection.

  22. 4 out of 5

    Juan

    The content is good but I feel it's more of a reference book than an introductory one. The content the book covers is very broad. Covering almost everything you expect but if you are a begginer you may need a book that is more extensive on the explanations. Nonetheless it includes a very good apendix. I did not read the whole book as I feel is more of a reference and I don't think this book should be anyone first read on algorithims. The tittle might be a bit of a misnomer. P.S.: The indexes of the The content is good but I feel it's more of a reference book than an introductory one. The content the book covers is very broad. Covering almost everything you expect but if you are a begginer you may need a book that is more extensive on the explanations. Nonetheless it includes a very good apendix. I did not read the whole book as I feel is more of a reference and I don't think this book should be anyone first read on algorithims. The tittle might be a bit of a misnomer. P.S.: The indexes of the arrays of the algorithms the book describes start at 1 which is some times annoying if you are used to 0.

  23. 5 out of 5

    Prashant Singh

    - This book is not for beginners . You must know the basics of topics and code and after that you can go to this book to understand the correctness of the algorithm and time complexity . - For example , this book explains why dynamic programming solution for Matrix Chain multiplication works . - Each chapter of the book is independent from other . You can select a topic and directly read it . - Matrix chain multiplication order and log cutter problem are very well explained . - KMP algorithm for s - This book is not for beginners . You must know the basics of topics and code and after that you can go to this book to understand the correctness of the algorithm and time complexity . - For example , this book explains why dynamic programming solution for Matrix Chain multiplication works . - Each chapter of the book is independent from other . You can select a topic and directly read it . - Matrix chain multiplication order and log cutter problem are very well explained . - KMP algorithm for substring search is not explained well .

  24. 4 out of 5

    Abdurrezzak Efe

    This is undoubtedly one of the most famous CS books out there. It deserves its reputation; it has a great scope of topics, a lot of fantastic algorithms, a good structure that gives whatever is necessary before any subject etc. However, the book, in some points, fails to provide the reader with sufficient intuition on the procedure. Also in some places, there is unnecessary detailed work. Anyways, reading/studying this book one can master algorithms which are very essential for Computer Science.

  25. 4 out of 5

    Ericka

    Before there were computers, there were algorithms On hold! I finished my first course on Algorithms with some chapters of this book, but as my first introduction to analyzing algorithms it wasn't that good or clear. I hope next semester I can go back with more background and study it properly, because it does have some good insights! I especially liked that it explained complex ideas, because every one that's starting in the world of algorithms needs to familiarize asap with these concepts!

  26. 4 out of 5

    Thea Yusuf

    A clear and great explanations of the concepts of algorithms and data structures. Highly recommended for CS students and those who are going to have an interview in tech companies for grasping every algorithm and data structures concepts. :) What I am not satisfied from this book is they are not dive deep enough to each of algorithm practices and the explanation about how to optimize your algorithm with time and space complexity is a bit tad. Still great for explaining basic understanding and con A clear and great explanations of the concepts of algorithms and data structures. Highly recommended for CS students and those who are going to have an interview in tech companies for grasping every algorithm and data structures concepts. :) What I am not satisfied from this book is they are not dive deep enough to each of algorithm practices and the explanation about how to optimize your algorithm with time and space complexity is a bit tad. Still great for explaining basic understanding and concepts of algorithm and data structures though.

  27. 4 out of 5

    Aniket Joshi

    Don’t just read the book as a book, use it as a reference, i know it is easier said than done, apart from the formal theorems and proofs do give it a try to solve the problems, and actually implement tue algorithms, the only part i did not like is how they have explained is the matrix chain multiplication

  28. 4 out of 5

    Endilie Yacop Sucipto

    CLRS is without doubt one of the best book when learning about Algorithms, sometimes called as the "bible" of algorithm. However, while it is more of a reference book with very lengthy pages, it lacks some in-depth explanation on certain parts. I guess that's fine because it is indeed an "introductory" book.

  29. 5 out of 5

    Samantha

    It's great that the authors understand what in the fuck they're talking about. It'd be even better if they tried to make sure that other people could understand it too. I gave up on this book after its explanation on the FFT seemed like it was deliberately trying to make the whole of it completely unintelligible. This is definitely not an "Introduction" to anything book.

  30. 4 out of 5

    Sarot Busala

    Like the Bible of the field. This book helped my way through computer olympic camp(IOI selection camp) back in high-school. Also prepared necessary fundamental skill sets for my further study from that point. I’m still grateful until now!

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