Category Archives: In English

Posts in English

Making sense: The API is FREE. Use it today and give us your feedback!

What if you have a bunch of or just one long text in any language and none of summarisation tools work for you?

If you have been in such a situation and also you have texts from social media or news sources that you cannot always trust in terms of how clean of noise they are, do they have URLs, hashtags, people names, addresses and so on.

And if you wanted to sift through the texts with some filter, like I want only nouns and only verbs to capture who did what.
Or I want only adjectives and nouns to capture with what colour do texts describe arbitrary objects.
Or I just want to have links out of all texts.

Now you can do all of that with one call to our SemanticCloud API.

Let’s pick the following tweet with hashtags and an URL in it and a mix of two languages: Russian and English:
Я голосую за сильного президента, за сильную независимую Россию и за тех, кто привык спрашивать только с себя, а не винить в своей лени остальных! I vote for a strong president, for a strong Russia! #выборыпрезидента #RussiaElections2018 #ЯГолосую #ЗаПутина #Putin

And let’s ask the system to output nouns, verbs, adverbs, adjectives, names, hyperlinks.

Two top words by count are: strong and сильный (translation pair)

“word”: “strong”,
“stem”: “strong”,
“partOfSpeech”: “Unknown”,
“count”: 2,
“lemma”: false,
“keyword”: false

“word”: “сильный”,
“stem”: “сильный”,
“partOfSpeech”: “Adjective”,
“count”: 2,
“lemma”: true,
“keyword”: false

But we also parsed the words out of hashtags:

“word”: “яголосую”,
“stem”: “яголос”,
“partOfSpeech”: “Unknown”,
“count”: 1,
“lemma”: false,
“keyword”: false

“word”: “выборыпрезидента”,
“stem”: “выборыпрезидент”,
“partOfSpeech”: “Unknown”,
“count”: 1,
“lemma”: false,
“keyword”: false

and a URL:

“word”: “”,
“stem”: “”,
“partOfSpeech”: “Hyperlink”,
“count”: 1,
“lemma”: false,
“keyword”: false

In addition we can ask the API to give us only top N words (by frequencies) along with lemmas (where applicable). And, more importantly, we can ask to count our secret word, that we are monitoring. Whether or not our secret word is present in the texts, it will be returned back:

“word”: “петербург”,
“stem”: “петербург”,
“partOfSpeech”: “Noun”,
“count”: 0,
“lemma”: true,
“keyword”: true

The API is FREE. Use it today and give us your feedback!


Insider team

Feedback API to improve sentiment detection algorithm

We are pleased to announce the addition of a new feature in RussianSentimentAnalyzer API: feedback endpoint. Using the endpoint you can provide correct sentiment label for an earlier submitted text, if you disagree with the API’s label. With this information we will automatically adjust performance of the sentiment prediction after accumulating enough of ‘text,correct label’ pairs.

So from now on you can train the algorithm behind the RussianSentimentAnalyzer API!

Did you have a chance to visit our brand new web-site? Please do visit and let us know, what you think!

Insider team

NEW API: ConnectedWords

Hello and Happy New Year!

New Year – New API. We have launched new API called ConnectedWords. We have trained a neural network using word2vec approach on a number of English texts. As input you can supply an array of keywords for which you’d like to get another list of connected or related words.


Available end-points:

Here is an example:

For word “launch” the API produces the following connected words:

“launched 0.5948931514907372”,
“ariane 0.5640206606244647”,
“icbm 0.532163213444619”,
“canaveral 0.5222400316699805”,
“rocket 0.5168188279637889”,
“launcher 0.5066764146199603”,
“suborbital 0.4987842348018603”,
“landing 0.49743730683360354”,
“expendable 0.49456818497947097”,
“agena 0.49325088465809586”,
“orbiter 0.4930563861239534”,
“shuttle 0.48127536803463045”,
“unmanned 0.47977178154360445”,
“launches 0.47013505662020805”,
“sputnik 0.4690193780888272”,
“bomarc 0.46608954818339043”,
“mission 0.4622460565342408”,
“redstone 0.4509777243147255”,
“gliders 0.4493604525398496”,
“missile 0.4388378398880377”,
“abort 0.4322835796211848”,
“rockets 0.4255249811253634”,
“lgm 0.42401975940492775”,
“launching 0.42055305756491634”,
“spacecraft 0.42044358977136653”,
“warhead 0.4203600640856848”,
“manned 0.4196165464952628”,
“skylab 0.417352627778655”,
“spaceflight 0.41261142646271765”,
“payloads 0.41167406251520333”,
“operational 0.41030200304930986”,
“refueling 0.41015588246409607”,
“orbit 0.4054650313323691”,
“extravehicular 0.4040691414909361”,
“icbms 0.4037563327101452”,
“hotol 0.4027989227897706”,
“sts 0.400049473907643”,
“saturn 0.399919637824496”,
“payload 0.398525218766963”,
“bm 0.3965859062493564”

How can one use the API?

1. Making your search engine smarter: expand the result set to documents containing related words. This helps you solve the issue of zero hit searches.

2. Spice up your writing. Are you a journalist / blogger / student and would like to add a flavour to your text? Send in a few words and get a set of words, that might help make your texts more interesting and engaging.

In the future we would like to add support for other languages and train on different types of texts, like social media, news, blogs etc. If you have more ideas for how to make the system more useful for your needs, get in touch!


Fuxi API: Normalized sentiment strength (release 1.5.2)

We are pleased to announce the release 1.5.2 of Fuxi API for Chinese sentiment analysis. In this release we have bounded the sentiment strength (previously unbounded integer value) into a range [-1, 0, 1]. The value is a floating number and is normalized.

Hope you enjoy using the API & let us know any feedback / suggestions you might have!

Insider team

Fuxi API 1.4 released

We are pleased to announce the 1.4 release of the Chinese sentiment analysis Fuxi API. In this release we improved the detection quality a lot. Feel free to send us your feedback. Remember, that on-premise installations are also possible and the API is very lightweight in terms of memory and CPU consumption. 40+ companies and individuals already trust Fuxi API, we will be more than happy to see you on board!

Enjoy 1.4 release of Fuxi #api for #Chinese#sentiment #analysis on Mashape and RapidAPI:

https://Fuxi API

Quick message from the Insider team. We have moved the Fuxi API to SSL. This means, that not only the communication from your systems to mashape is secure, but also the communication from mashape onward to our servers running Fuxi API is secure.

There is no action required from your part to continue using the Fuxi API for Chinese sentiment analysis.

Thank you!
Insider team