Category Archives: In English

Posts in English

New DocTop API: identify meaningful topics in documents in 8 languages

We are excited to share the news: we have just launched new DocTop API for identifying and extracting meaningful topics from documents in English, French, German, Dutch, Italian, Portuguese, Greek and Spanish.

You can send multiple documents for analysis in a single JSON request. First 10 documents will be analyzed.

Curiosity rover exploring topics in text data

When do you want to extract topics from unstructured text? Here are a few reasons:

  • Find out what are the top standing out topics that your documents are talking about.
  • Identify trends. For this, you can systematically collect topics for new documents and compare with volumes of same topics in the past.
  • Tag documents with topics to group them.
  • Allow searching within topics of interest to get focused search results.
  • Track topics to make a sense of the textual data being produced and become more data driven.
  • Correlate topics with other facets of your data, like geography, user age brackets, gender etc.

Here is an example of how to use the API for English:

[
	{
		"article_id": 1,
		"text": "San Francisco considers banning sidewalk delivery robots"
        }	
]

In response to the request above you’ll get an array of identified topics:

[
  {
    "article_id":1,
    "topics":[
         "sidewalk delivery robots"
         "san francisco"
    ]
  }
]

And here is the request/response pair for a text in Spanish:

[
	{
		"article_id": 1,
		"text": "Apple está buscando comprar una startup del Reino Unido por mil millones de dólares"
    }	
]
[
  {
    "article_id":1,
    "topics":[
       "reino unido"
       "millones"
       "startup"
       "dólares"
       "apple"
    ]
  }
]

Subscribe to the DocTop API today and test it out on free 100 texts in any supported language!

Russian topics quality improved

Hello our dear users,

We are happy to announce the improvements in the quality of topics produced for texts in Russian.

The trick with Russian and similar languages (Ukrainian, Finnish, Belorussian, Polish) is rich morphology: lots of word endings (surface forms), grammatical cases will lead to abrupt topics or topics in a wrong case.

We have implemented additional analysis techniques that will compute base forms when applicable and remove prepositions on the boundaries of topics.

Enjoy and remember that topics are your gateway to categorizing large number of texts and bringing structure to unstructured.

The update is immediately available for all our users.

Consume the Topic API today: https://rapidapi.com/dmitrykey/api/topicapi

Insider team

More languages to the mix

Dear users!

We are super thrilled to announce the support of virtually any language in TopicAPI. Upload and gets topics for your articles in German or Russian. We plan to add more languages in the coming weeks. Please let us know what language you would like the most: https://goo.gl/forms/5RtE8ywHY2GYrTYH2

Notice, that we have updated the documentation to reflect the multi-language feature: you need to supply a language code in the URL path to make sure your content is properly processed. See more here: https://market.mashape.com/dmitrykey/topicapi

Happy coming holidays and many insightful topics in your content!

Insider

Mashape

Мы гипер рады сообщить о том, что теперь TopicAPI поддерживает практически любой язык. Сейчас это русский и немецкий. Пожалуйста, дайте нам знать, какой язык вы хотели бы видеть в системе в первую очередь: https://goo.gl/forms/5RtE8ywHY2GYrTYH2

Обращаем ваше внимание, что мы изменили документацию к API: https://market.mashape.com/dmitrykey/topicapi

Счастливых праздников!

Insider

Sample code for grouping articles into themes

In this post we would like to share with you Java code snippets, that allow for loading data into our Topic API. The idea of the topic API is that it allows you to group your articles / posts / tweets / documents into topical themes and also search in the content.

In order to navigate oceans of textual data and extract useful structures from your content lakes search is one of the most common way to empower your journey. But once you have found thousands and thousands of matches, you still have the problem of the data overload. Topical grouping can help.

All code in this post you can find in our public GitHub repository. We further assume, that your article content is stored in a MySQL database. Using mybatis we load the articles with https://github.com/semanticanalyzer/nlproc_sdk_sample_code/blob/master/src/main/resources/mappers/ArticleEntryMapper.xml.

TopicLoader class takes care of doing it all: loading articles from the DB, forming a JSON request to the Topic API and uploading the relevant fields.

This main class takes single command line argument: resource_id, which matches onto the field of articles DB table in https://github.com/semanticanalyzer/nlproc_sdk_sample_code/blob/master/src/main/resources/mappers/ArticleEntryMapper.xml.

The method uploadDBEntries will load the articles entries from the DB and upload to the Topic API one by one. Note, that if your content is not very large in size (tweet size), then you can upload several posts in one single request (up to 50 at a time).

To upload an article to the Topic API we use the following code:

 
    private void uploadArticleToTopicAPI(ArticleEntry x) {
        GsonBuilder builder = new GsonBuilder();
        Gson gson = builder.create();

        try {
            String body = "[" + gson.toJson(x) + "]";

            System.out.println("Sending body for id: " + x.getId());

            HttpResponse<JsonNode> response = Unirest.post("https://dmitrykey-insiderapi-v1.p.mashape.com/articles/uploadJson")
                    .header("X-Mashape-Key", mashapeKey)
                    .header("Content-Type", "application/json")
                    .header("Accept", "application/json")
                    .body(body)
                    .asJson();

            System.out.println("TopicAPI response:" + response.getBody().toString());
        } catch (UnirestException e) {
            log.error("Error: {}", e);
            System.err.println("Error: " + e.getMessage());
        }
    }

Remember that you need to obtain the mashapeKey by subscribing to the API and checking the documentation, where you will find the key already pre-inserted: https://market.mashape.com/dmitrykey/topicapi.

After the upload is complete, the articles end up in a search engine on the backend of the Topic API. You can start triggering the search requests and getting back nice themes. In this example below I have uploaded about 10,000 Russian texts and gotten topics:

Что Говорят # What they say
Большие деньги # Big money
Беларуский Бренд # Belorussian brand
Для Ребенка # For a kid
Как Выглядит работа # How a job looks like
Как Заработать # How to earn money
В Минском Масс-маркете # In a grocery store of Minsk
Женщины # Women

Halloween launches / Релизы на Хеллоуин

We are pleased to report new features in the Topic API — system for realtime topic clustering of documents: articles, blog posts, tweets.

Mashape

We have improved the algorithm to avoid situations where a preposition would be omitted — helps a lot for Russian.

We have added a possibility to filter clusters by time range: use params startDate and endDate in the format yyyy-MM-dd. This feature should allow you to build trends over time!

We made the /articles/cluster end point to support GET — more sensible when integrating with frontends

Enjoy and Happy Halloween!

Мы рады сообщить о новых фичах в Topic API — системе для построения тематических кластеров документов: статей, блог-постов, твитов.

Мы улучшили алгоритм таким образом, чтобы названия кластеров включали предлоги. Например, раньше кластер мог называется “Питере”, теперь он будет называться “В Питере” (конечно, в зависимости от ваших данных).

Теперь кластера можно строить для конкретного промежутка времени: используйте параметры startDate и endDate в формате yyyy-MM-dd. Теперь вы можете строить тренды!

Энд-пойнт /articles/cluster теперь доступен по GET — это более дружественный тип запроса для интеграции с фронтэндами.

Удачи и классного Хэллоуина!

Insider team / команда Insider

Text analytics APIs: simplified pricing

We focus a lot on unifying access to our text analytics APIs. One of such areas is pricing. We obviously want more users to have access to our systems at meaningful prices.

In the course of the last month we have unified and decreased prices for all our APIs. Here are the changes:

RSA API (entity level sentiment detection for Russian):
Overage fee for Basic plan is USD $0,02 (was: USD $0,05). This matches the overage fee on all other plans.
PRO plan is now USD $99 instead of $299.
ULTRA plan is now USD $199 instead of $350.

FUXI API (sentiment detection for Chinese):
We changed our subscription plan Basic to allow for 15,000 texts a month for just $10 instead of 500 / day.
PRO plan allows you to 100,000 texts a month for $99.

Topic API (searchable topics for texts in Russian)
Basic plan allows for sending 1,000 messages for $19. Remember, that one message can contain up to 50 texts. If you were only uploading texts you could upload 50,000 of them.

The following APIs continue to be FREE:

ConnectedWords (find semantically similar English words to the ones given)
SemanticCloud (frequency word clouds for Russian along with lemmas)

Our team is always listening to you, our users — let us know, what APIs you would like to have in addition, what features to existing APIs and what volumes you would like to handle.

Enjoy the journey of extracting signal from your textual lakes!

AI education. What market requires?

When you start looking at the field of AI (Artificial Intelligence) as a business leader or software developer you can get lost at first.

In this online seminar between Carine Simon, MIT (Boston, USA), Borys Pratsyuk, Ciklum, Valeria Zabolotna, UNIT.City (Kiev, Uktrain) and Dmitry Kan, Insider (Helsinki, Finland) you will learn:

  1. What formal AI education programs exist at MIT
  2. What industry expects of hires for AI role
  3. How to get started with AI as a practitioner — frameworks, hardware, communities

Seminar host: Misha Feldman

Hope you will enjoy the video and do let us know, if it was helpful for you!