<p>Word-vectors or so-called distributed representations have a long history by now, starting perhaps from work of S. Bengio (<em>Bengio, Y., Ducharme, R., &amp; Vincent, P. (2001).A neural probabilistic language model. NIPS.</em>) where he obtained word-vectors as by-product of training neural-net lanuage model.</p>

<p>A lot of researches demonstrated that these vectors do capture semantic relationship between words (see for example <a href="http://research.microsoft.com/pubs/206777/338_Paper.pdf" rel="noreferrer">http://research.microsoft.com/pubs/206777/338_Paper.pdf</a>). Also this important paper (<a href="http://arxiv.org/abs/1103.0398" rel="noreferrer">http://arxiv.org/abs/1103.0398</a>) by Collobert et al, is a good starting point with understanding word vectors, the way they are obtained and used. </p>

<p>Besides word2vec there is a lot of methods to obtain them. Expamples include SENNA embeddings by Collobert et al (<a href="http://ronan.collobert.com/senna/" rel="noreferrer">http://ronan.collobert.com/senna/</a>), RNN embeddings by T. Mikolov that can be computed using RNNToolkit (<a href="http://www.fit.vutbr.cz/~imikolov/rnnlm/" rel="noreferrer">http://www.fit.vutbr.cz/~imikolov/rnnlm/</a>) and much more. For English, ready-made embeddings can be downloaded from these web-sites. word2vec really uses skip-gram model (not neural network model).  Another fast code for computing  word representations is GloVe (<a href="http://www-nlp.stanford.edu/projects/glove/" rel="noreferrer">http://www-nlp.stanford.edu/projects/glove/</a>). It is an open question whatever deep neural networks are essential for obtaining good embeddings or not.</p>

<p>Depending of your application, you may prefer using different types of word-vectors, so its a good idea to try several popular algorithms and see what works better for you.  </p>
how to create word vector
<p>How to create word vector? I used one hot key to create word vector, but it is very huge and not generalized for similar semantic word. So I have heard about word vector using neural network that finds word similarity and word vector. So I wanted to know how to generate this vector (algorithm) or good material to start creating word vector ?.</p>