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sem_generate_keywords.ipynb

+66-13
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@@ -28,7 +28,7 @@
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},
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"outputs": [],
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"source": [
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"import csv # the main package simply to save the keywords table to a file"
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"import csv # to save the keywords table to a file"
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]
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},
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{
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"For this example we will be generating keywords for an imaginary business that sells used cars online.\n",
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"For simplicity, let's assume that the following are available as products and keywords:\n",
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"\n",
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" 1. Products: 'honda', 'honda accord', 'honda civic', 'toyota', 'toyota camry'\n",
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" 2. Keywords: 'buy', 'price', 'second hand\n",
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"1. Products: 'honda', 'honda accord', 'honda civic', 'toyota', 'toyota camry'\n",
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"2. Keywords: 'buy', 'price', 'second hand'\n",
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"\n",
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" The end result we are looking for, would be something like this:\n",
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"The end result we are looking for, would be something like this:\n",
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"\n",
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" |Campaign | Ad Group | Keyword | Criterion Type |\n",
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" |-----------|--------------|--------------------------|-----------------|\n",
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" |SEM Cars | Toyota | buy toyota | Exact |\n",
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" |SEM Cars | Toyota | buy toyota | Phrase |\n",
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" |SEM Cars | Honda Accord | buy honda accord | Exact |\n",
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" |SEM Cars | Honda Accord | honda accord second hand | Exact |\n",
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" |etc...\n",
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"\n",
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"|Campaign | Ad Group | Keyword | Criterion Type |\n",
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"|-----------|--------------|--------------------------|-----------------|\n",
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"|SEM Cars | Toyota | buy toyota | Exact |\n",
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"|SEM Cars | Toyota | buy toyota | Phrase |\n",
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"|SEM Cars | Honda Accord | buy honda accord | Exact |\n",
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"|SEM Cars | Honda Accord | honda accord second hand | Exact |\n",
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"etc...\n",
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"\n",
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"You can easily imagine how large the combinations would become when we have, let's say 20 car makes, with ten models each, together with 25-30 different keywords the list would be in the tens of thousands.\n",
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"So we need a systematic way of knowing how to generate them, as well as knowing that we can make structural changes across all combinations whenever we need (and we will have to during the course of running the campaigns).\n",
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"\n",
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"\n",
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"| location | make | model |\n",
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"|----------+--------+--------|\n",
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"|----------|--------|--------|\n",
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"| Tokyo | honda | civic |\n",
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"| Tokyo | honda | accord |\n",
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"| Tokyo | toyota | camry |\n",
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}
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],
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"metadata": {
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"hide_input": false,
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"kernelspec": {
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"display_name": "Python 3",
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"name": "python3"
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},
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"name": "sem_generate_keywords.ipynb"
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"language_info": {
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"name": "ipython",
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.1"
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"name": "sem_generate_keywords.ipynb",
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"library": "var_list.py",
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"varRefreshCmd": "print(var_dic_list())"
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"delete_cmd_postfix": ") ",
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"library": "var_list.r",
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"varRefreshCmd": "cat(var_dic_list()) "
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"nbformat": 4,
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"nbformat_minor": 2

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