Are you looking for ways to increase your website ranking? Trying to figure out how to be on top of the google search engine pages? Well, the information below is going to be your best friend. The website is the heart of any business in this digital world. The most important part of traffic is from organic searches.

The use of semantic descriptions in data intensive domains require a systematic model for linking semantic descriptions with their manifestations in fragments of heterogeneous information and data objects. Such information heterogeneity requires a fragment model that is general enough to support the specification of anchors from conceptual models to multiple types of information artifacts. While diverse proposals of anchoring models exist in the literature, they are usually focused in audiovisual information. We propose a generalized fragment model that can be instantiated to different kinds of information artifacts. Our objective is to systematize the way in which fragments and anchors can be described in conceptual models, without committing to a specific vocabulary.

Over the past year, AI systems have made huge strides in their ability to generate convincing text, churning out everything from song lyrics to short stories. Experts have warned that these tools could be used to spread political disinformation, but there's another target that's equally plausible and potentially more lucrative: gaming Google. Instead of being used to create fake news, AI could churn out infinite blogs, websites, and marketing spam. The content would be cheap to produce and stuffed full of relevant keywords. But like most AI-generated text, it would only have surface meaning, with little correspondence to the real world.

Your machine learning models need training data to make sure that your algorithms are continually optimized. But not just any data – they need large, high-quality, human-annotated datasets. Humans are simply better than computers at managing subjectivity, understanding intent, and coping with ambiguity. Appen's global, curated crowd allows you to collect the amount of quality data samples needed to optimize your algorithm, in your desired timeframe. Leverage the Appen Global platform to gain efficiencies in your data collection efforts and gather large volumes of high-quality datasets to quickly train your machine learning model.

Entity recommendation, providing search users with an improved experience via assisting them in finding related entities for a given query, has become an indispensable feature of today's search engines. Existing studies typically only consider the queries with explicit entities. They usually fail to handle complex queries that without entities, such as "what food is good for cold weather", because their models could not infer the underlying meaning of the input text. In this work, we believe that contexts convey valuable evidence that could facilitate the semantic modeling of queries, and take them into consideration for entity recommendation. In order to better model the semantics of queries and entities, we learn the representation of queries and entities jointly with attentive deep neural networks. We evaluate our approach using large-scale, real-world search logs from a widely used commercial Chinese search engine. Our system has been deployed in ShenMa Search Engine and you can fetch it in UC Browser of Alibaba. Results from online A/B test suggest that the impression efficiency of click-through rate increased by 5.1% and page view increased by 5.5%.

Google entering verticals and competing directly against publishers, advancements in machine learning and AI and zero-click searches are the trends most likely to affect SEO in the next three years, according to a SparkToro survey of over 1,500 SEOs. Trends that are here to stay? Respondents were presented with a list of choices and asked, "How much of an impact do you believe the following trends will have on SEO in the next 3 years?" Options were ranked on a zero-to-four scale; zero meaning "no impact" and four meaning "huge impact." The trend that professionals responded were least likely to affect SEO included outcomes from US Congressional and Department of Justice investigations, visual search advances and "content-nudging" products such as Google Discover.

Google's goal has always been to organize the world's information, and its first target was the commercial web. Now, it wants to do the same for the scientific community with a new search engine for datasets. The service, called Dataset Search, launches today, and will be a companion of sorts to Google Scholar, the company's popular search engine for academic studies and reports. Institutions that publish their data online, like universities and governments, will need to include metadata tags in their webpages that describe their data, including who created it, when it was published, how it was collected, and so on. This information will then be indexed by Dataset Search and combined with input from Google's Knowledge Graph.

We present improvements in maximum a-posteriori inference for Markov Logic, a widely used SRL formalism. Inferring the most probable world for Markov Logic is NP-hard in general. Several approaches, including Cutting Plane Aggregation (CPA), perform inference through translation to Integer Linear Programs. Aggregation exploits context-specific symmetries independently of evidence and reduces the size of the program. We illustrate much more symmetries occurring in long ground clauses that are ignored by CPA and can be exploited by higher-order aggregations. We propose Full-Constraint-Aggregation, a superior algorithm to CPA which exploits the ignored symmetries via a lifted translation method and some constraint relaxations. RDBMS and heuristic techniques are involved to improve the overall performance. We introduce Xeggora as an evolutionary extension of RockIt, the query engine that uses CPA. Xeggora evaluation on real-world benchmarks shows progress in efficiency compared to RockIt especially for models with long formulas.

Business firms who sell their products and services online, want to enhance the visibility of their website so that they can get top ranking in SERP(Search Engine Result Page; Google, Yahoo, Bing..). SEO is the process of optimizing the website to get organic or natural traffic and ranking of your targeted keywords. Ranking of the website is based on what the search engine considers most relevant to users. All search engines provide the best info for their users. So if you have a website and you want to increase the visibility of your website and want to see your website at the top rank of search engine's results, you will definitely need SEO software that helps find keywords you can rank for, links you can get and On-Page optimization guaranteed to increase rankings on search engines.

Google My Business is now providing insights to business owners about what their business is known for, according to customers. A new addition to the Google My Business insights section for cafes and restaurants offers data about subjective attributes, which are based on customers' opinions. We've launched subjective attributes to provide more information in your insights tab! Customers of restaurants and cafes can submit subjective attributes to help you and their fellow customers. When submitting a Google review, customers can add a variety of subjective attributes. If a particular attribute is submitted frequently enough, it will appear on the listing for others to see.