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A web application for interactive visualization of semantic graphs generated from naruhodo.

First you need to install the latest version of naruhodo and make sure it is working properly. For installation and setup of naruhodo, refer to this link.

Then you need to clone this repository to your local disk:

git clone https://github.com/superkerokero/naruhodo-viewer.git

Go to the directory of the app you have cloned, and edit config.json file in the root folder:

{
    "mp": false,
    "wv": ""
}

If mp is set to true, naruhodo will be run in multiprocessing mode(may provide speedup for multi-processor cpus), the default value is false.

If you want to use experimental coreference resolution function in naruhodo based on word embeddings, you need to change wv to the string of your word2vec model path. Otherwise leave it as an empty string.

A complete list of available config parameters and corresponding default values can be found in config-parameters section.

Next, open a terminal from the root folder of the repository, and use the following command to start the web server:

python viewer.py config.json

Now you can open your browser and go to the following address to use the app.

http://localhost:8000

• You can use the input bar to add contents to the graph.

• Use Setting button to toggle setting menu.

• When you move your cursor over a node in the graph(or touch a node on mobile devices), a popup window will show you the original text that contains this node and its relative position in the input context.

• You can also add contents of webpages into graph directly using naruhodo's built-in scraper. But please be careful with large amount of texts, since too many nodes and edges in the graph will degrade the webapp's performance significantly.

• You can use clustering functions in the setting menu to cluster certain nodes together. A cluster node is repsented in a database shape like in the following snapshot. You can open a cluster by clicking the cluster node. Currently 3 types of clustering are supported:
  • Cluster by synonyms
  • Cluster by coreferences
  • Cluster by meaning(for meaningless stop words)
• You can also use ClusterAll and OpenAll buttons to cluster or open all available clustering types at once.